session |
{'_domain': None, '_path': '/', '_accessed_time': 1750618833.5804265, '_creation_time': 1750618833.5804265, 'initial_search_params': {'facet.field': ['organization', 'tags', 'res_format', 'license_id'], 'fq': [' owner_org:"9a7d2a53-21f6-412a-afb9-a15122df0640" -dataset_type:harvest', '+site_id:"default"', '+state:active', '+permission_labels:("public")'], 'q': '*:*', 'rows': 21, 'start': 0, 'df': 'text', 'mm': '5<-4 9<-90%', 'defType': 'edismax', 'bf': '0', 'qf': 'title^5 text', 'sort': 'score desc, metadata_modified desc', 'fl': 'id validated_data_dict', 'facet': 'true', 'facet.limit': '50', 'facet.mincount': 1, 'wt': 'json', 'tie': '0.1', 'q.op': 'AND', 'extras': {}}, 'search_results_final': {'count': 135, 'facets': {'organization': {'darus': 135}, 'tags': {'chemistry': 135, 'physics': 36, 'experimental-data': 26, 'computer-and-information-science': 24, 'engineering': 24, 'medicine-health-and-life-sciences': 15, 'molecular-dynamics-simulation': 14, 'metathesis': 12, 'catalysis': 10, 'confinement': 10, 'earth-and-environmental-sciences': 10, 'excess-properties': 10, 'fair': 10, 'fair-data-principles': 10, 'liquid-mixtures': 10, 'mathematical-sciences': 10, 'molybdenum': 10, 'transferability-of-force-fields': 10, 'porous-media': 7, 'tungsten': 7, 'gromacs': 6, 'image-data': 6, 'metal-complex': 6, 'micro-x-ray-computed-tomography-micro-xrct': 6, 'thermoml': 6, 'transition-metal': 6, 'adsorption': 5, 'asymmetric-catalysis': 5, 'diene-ligands': 5, 'dna-methylation': 5, 'dna-methyltransferase': 5, 'enzyme-assay': 5, 'heterogeneous-catalysis': 5, 'rhodium-catalysis': 5, 'sodium-chloride': 5, 'alkylidene-group': 4, 'biotechnology': 4, 'dnmt3a': 4, 'enzymeml': 4, 'enzymology': 4, 'input-files-for-molecular-dynamics-simulations-with-gromacs': 4, 'kinetics': 4, 'magnesium-sulfate': 4, 'n-heterocyclic-carbene': 4, 'thermoml-file': 4, 'zeolite': 4, 'biomineralization': 3, 'c-c-coupling': 3, 'covalent-organic-framework': 3, 'density-functional-theory-dft': 3}, 'res_format': {'HTML': 135}, 'license_id': {'': 135}}, 'results': [{'author': 'Ziegler, Felix', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-832', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:23.488051', 'metadata_modified': '2023-05-08T19:14:23.488056', 'name': 'doi-10-18419-darus-832', 'notes': 'This paper addresses the synthesis of macrocyclic molecules by a spatial confinement effect in SBA-15. Various aspects such as concentration dependence, substrate size and temperature dependence have been discussed.<br><br> \n\nIn the attached data you will find all NMR spectra of the performed reactions as well as the sorption measurements, ICP analyses, elemental analyses, Maldi-TOF and SEM pictures. All data are sorted according to the labeling in the paper.<br><br>\n\nAll primary data files and processed data of the journal article from the Buchmeiser group and links to related data sets from other groups.', 'num_resources': 1, 'num_tags': 5, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Olefin Metathesis in Confined Geometries: A Biomimetic Approach toward Selective Macrocyclization Data Buchmeiser', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Ziegler, Felix'}, {'key': 'creator', 'value': 'Ziegler, Felix'}, {'key': 'date', 'value': '2020-12-23T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-832'}, {'key': 'metadata_modified', 'value': '2022-11-29T01:00:03'}, {'key': 'relation', 'value': 'Felix Ziegler, Johannes Teske, Iris Elser, Michael Dyballa, Wolfgang Frey, Hamzeh Kraus, Niels Hansen, Julia Rybka, Ulrich Tallarek, Michael R. Buchmeiser CCDC 1942469: Experimental Crystal Structure Determination, 2019, DOI: <a href="https://doi.org/10.5517/ccdc.csd.cc23699y">10.5517/ccdc.csd.cc23699y</a>'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '8a7e8a72-295f-4400-83e5-15abf928ef90'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:23.489548', 'format': 'HTML', 'hash': '', 'id': 'ddab5dd7-345f-462e-bc1c-096ad5087484', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:23.472814', 'mimetype': None, 'mimetype_inner': None, 'name': 'Olefin Metathesis in Confined Geometries: A Biomimetic Approach toward Selective Macrocyclization Data Buchmeiser', 'package_id': 'doi-10-18419-darus-832', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-832', 'url_type': None}], 'tags': [{'display_name': 'catalysis', 'id': '109d3c51-8485-4605-ad00-c576d7092a7a', 'name': 'catalysis', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'confinement', 'id': '6cb7505c-f92e-435f-a1dc-e7542d4a061a', 'name': 'confinement', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'experimental-data', 'id': '2468cb76-4757-4ec7-be40-8da1b05b5f1c', 'name': 'experimental-data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'metathesis', 'id': '62ec03a6-9504-48c7-9261-c43ce49d375b', 'name': 'metathesis', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Dietrich, Clarissa, Collings, Peter J., Sottmann, Thomas, Rudquist, Per, Giesselmann, Frank', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-746', 'isopen': False, 'language': 'English', 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:21.404738', 'metadata_modified': '2023-05-08T19:14:21.404744', 'name': 'doi-10-18419-darus-746', 'notes': 'Depolarized dynamic light scattering (DDLS) data, fit routine & fitting results', 'num_resources': 1, 'num_tags': 8, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Data from "Extremely Small Twist Elastic Constants in Lyotropic Nematic Liquid Crystals"', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Giesselmann, Frank'}, {'key': 'creator', 'value': 'Dietrich, Clarissa'}, {'key': 'date', 'value': '2020-10-01T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-746'}, {'key': 'metadata_modified', 'value': '2022-11-29T01:00:03'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '40c93ac6-c256-4bc2-8fec-b1049c774f9c'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:21.413652', 'format': 'HTML', 'hash': '', 'id': 'a6383ffc-7699-439d-a2aa-2b0d438934c6', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:21.393478', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data from "Extremely Small Twist Elastic Constants in Lyotropic Nematic Liquid Crystals"', 'package_id': 'doi-10-18419-darus-746', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-746', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'dynamic-light-scattering', 'id': '2ebf7a50-4280-4665-bf95-cb2d429c30ed', 'name': 'dynamic-light-scattering', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'experimental-data', 'id': '2468cb76-4757-4ec7-be40-8da1b05b5f1c', 'name': 'experimental-data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'liquid-crystals', 'id': '12cef04b-0f3c-4c24-8d63-a698bcf07b06', 'name': 'liquid-crystals', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'lyotropic-phases', 'id': '8a159722-4bfa-47e4-97a2-b1a89aff078a', 'name': 'lyotropic-phases', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physics', 'id': '820fb04d-8f9c-45ca-9a54-9054d91e527b', 'name': 'physics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'surfactants', 'id': 'ee1c583b-6735-4491-b64f-ab8d7c4922c0', 'name': 'surfactants', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'viscoelastic-properties', 'id': '63ae8ae5-795c-4dc6-9a55-ebc5cf898057', 'name': 'viscoelastic-properties', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Kraus, Hamzeh, Rybka, Julia, Hansen, Niels', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-488', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:17.927570', 'metadata_modified': '2023-05-08T19:14:17.927576', 'name': 'doi-10-18419-darus-488', 'notes': 'This dataset contains simulation input files in GROMACS format accompanying the mentioned publication.<br>\n\nStructure, topology and simulation parameter-files are provided for six simulations - two pore sizes of 9nm and 6nm, each with simulations of pure substrate, pure product and a mixture of both, each with benzene as solute. Both pore-sizes are functionalized with epoxide groups on the inside and TMS groups on the outside surface. Furthermore each pore has two catalytic centers placed point-symmetrical towards each other.<br>\n\nThe simulation is divided in three steps, an energy-minimization, an NVT equilibration and finally the NVT production simulation run.', 'num_resources': 1, 'num_tags': 7, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': "Supplementary material for 'Computational study of confinement effects in molecular heterogeneous catalysis'", 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Kraus, Hamzeh'}, {'key': 'creator', 'value': 'Kraus, Hamzeh'}, {'key': 'date', 'value': '2022-01-11T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-488'}, {'key': 'metadata_modified', 'value': '2022-11-29T01:00:03'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '7e6e0456-dc58-4e28-be86-8eaf11a56194'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:17.944612', 'format': 'HTML', 'hash': '', 'id': 'dbfc33a6-85a3-4c39-ba09-055e8fac99ef', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:17.916298', 'mimetype': None, 'mimetype_inner': None, 'name': "Supplementary material for 'Computational study of confinement effects in molecular heterogeneous catalysis'", 'package_id': 'doi-10-18419-darus-488', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-488', 'url_type': None}], 'tags': [{'display_name': 'alkene-metathesis', 'id': '716569f0-2680-405f-bbac-03183c4d0340', 'name': 'alkene-metathesis', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'computer-and-information-science', 'id': '75b28b6d-af69-4c24-9c9e-451d429aad9b', 'name': 'computer-and-information-science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'confinement', 'id': '6cb7505c-f92e-435f-a1dc-e7542d4a061a', 'name': 'confinement', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'input-files-for-molecular-dynamics-simulations-with-gromacs', 'id': '325f6a0c-b6ad-4844-ad0d-b5c60b38b9ca', 'name': 'input-files-for-molecular-dynamics-simulations-with-gromacs', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'molecular-dynamics-simulation', 'id': '0040c50a-44c0-4113-b945-716272c88419', 'name': 'molecular-dynamics-simulation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'olefin-metathesis', 'id': '8e5e9399-43f6-4546-a8dc-3dc6376d7c1f', 'name': 'olefin-metathesis', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Kraus, Hamzeh, Rybka, Julia', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-477', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:17.747036', 'metadata_modified': '2023-05-08T19:14:17.747040', 'name': 'doi-10-18419-darus-477', 'notes': 'This dataset contains simulation input files in GROMACS format accompanying the mentioned publication.\r\nStructure, topology and simulation parameter-files are provided for two simulations - an unmodified pore with a silanol surface and a modified pore with an unpolar DMDMS surface. Furthermore each pore has two catalytic centers placed point-symmetrical towards each other.\r\nThe simulation is divided in three steps, an energy-minimization, an NVT equilibration and finally the NVT production simulation run.', 'num_resources': 1, 'num_tags': 2, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': "Supplementary material for 'Olefin metathesis in confined geometries: a biomimetic approach towards selective macrocyclization'", 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Kraus, Hamzeh'}, {'key': 'creator', 'value': 'Kraus, Hamzeh'}, {'key': 'date', 'value': '2019-12-04T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-477'}, {'key': 'metadata_modified', 'value': '2022-11-29T01:00:03'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '2cf62b84-2d20-414b-817b-e8db66b83926'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:17.749970', 'format': 'HTML', 'hash': '', 'id': 'ed875bbe-cadf-4fe7-957d-896d67e423dc', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:17.741453', 'mimetype': None, 'mimetype_inner': None, 'name': "Supplementary material for 'Olefin metathesis in confined geometries: a biomimetic approach towards selective macrocyclization'", 'package_id': 'doi-10-18419-darus-477', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-477', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'input-files-for-molecular-dynamics-simulations-with-gromacs', 'id': '325f6a0c-b6ad-4844-ad0d-b5c60b38b9ca', 'name': 'input-files-for-molecular-dynamics-simulations-with-gromacs', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Dyballa, Michael', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3407', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:16.247895', 'metadata_modified': '2023-05-08T19:14:16.247901', 'name': 'doi-10-18419-darus-3407', 'notes': 'Original data (Catalytic measurements, Characterization) of the journal article mentioned under related publications from the Dyballa group can be found here. See <a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=201292">File Documentation.txt</a> for a mapping between the figures of the publication and the files in the dataset.', 'num_resources': 1, 'num_tags': 2, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Replication Data for: "Better Performance in C2‑Conversion to Aromatics by Optimized Feed and Catalysts"', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Dyballa, Michael'}, {'key': 'creator', 'value': 'Dyballa, Michael'}, {'key': 'date', 'value': '2023-04-14T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3407'}, {'key': 'metadata_modified', 'value': '2023-04-15T00:00:05'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': 'a173d46e-05e8-4a0f-b90a-9ba4ad225097'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:16.249219', 'format': 'HTML', 'hash': '', 'id': '00e24d06-5742-41ae-bec7-b7da541340ac', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:16.242419', 'mimetype': None, 'mimetype_inner': None, 'name': 'Replication Data for: "Better Performance in C2‑Conversion to Aromatics by Optimized Feed and Catalysts"', 'package_id': 'doi-10-18419-darus-3407', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3407', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'heterogeneous-catalysis', 'id': '86b5272a-37ca-43c8-b338-18e1995d1ff5', 'name': 'heterogeneous-catalysis', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Beurer, Ann-Katrin, Dieterich, Sonja, Solodenko, Helena, Kaya, Elif, Merdanoǧlu, Naǧme, Schmitz, Guido, Traa, Yvonne, Bruckner, Johanna R.', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3348', 'isopen': False, 'language': 'English', 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:14.269382', 'metadata_modified': '2023-05-08T19:14:14.269390', 'name': 'doi-10-18419-darus-3348', 'notes': 'All primary data files of measurements and processed data of the journal article "Comparative study of lattice parameter and pore size of ordered mesoporous silica materials using physisorption, SAXS measurements and transmission electron microscopy", are deposited. File types which are not easily readable have been converted to other formats, i.e. TIF and TXT, and have been deposited additionally. PDH files may be opened with the same applications as TXT files. <p> The dataset contains the following data: nitrogen physisorption measurements, small-angle X-ray scattering curves, transmission electron micrographs. The data is named according to the sample name. A short description of the samples is given in the following:\n<p>\n<p>\n<b>OMS_TLCT:</b> Ordered mesoporous silica material synthesized via true liquid crystal templating with hexadecylethyldimethylammonium chloride as surfactant\n<p>\n<p>\n<b>MCM-41:</b> Ordered mesoporous silica material synthesized via a cooperative self-assembly process with hexadecyltrimethylammonium chloride as surfactant\n<p>\n<p>\n<b>SBA-15:</b> Ordered mesoporous silica material synthesized via a cooperative self-assembly process with the poloxamer P123 as surfactant\n<p>\n<p>\n<b>SBA-15_sa:</b> Ordered mesoporous silica material synthesized via a cooperative self-assembly process with the poloxamer P123 as surfactant and n-decane as swelling agent', 'num_resources': 1, 'num_tags': 7, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Replication data for: "Comparative study of lattice parameter and pore size of ordered mesoporous silica materials using physisorption, SAXS measurements and transmission electron microscopy"', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Bruckner, Johanna R.'}, {'key': 'creator', 'value': 'Beurer, Ann-Katrin'}, {'key': 'date', 'value': '2023-04-26T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3348'}, {'key': 'metadata_modified', 'value': '2023-04-27T00:00:05'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '4ba7e0d2-66af-42a1-841a-08309a0fe916'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:14.270952', 'format': 'HTML', 'hash': '', 'id': 'b1f5d1e6-e81e-4fdd-ac16-40f6a751230f', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:14.258902', 'mimetype': None, 'mimetype_inner': None, 'name': 'Replication data for: "Comparative study of lattice parameter and pore size of ordered mesoporous silica materials using physisorption, SAXS measurements and transmission electron microscopy"', 'package_id': 'doi-10-18419-darus-3348', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3348', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'experimental-data', 'id': '2468cb76-4757-4ec7-be40-8da1b05b5f1c', 'name': 'experimental-data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'mcm-41', 'id': 'dc3b63ce-cf26-4561-acb4-6d9af046e7a0', 'name': 'mcm-41', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'mesoporous-silica', 'id': '2383957f-1ab0-4a4c-be9c-8b415ebe1f72', 'name': 'mesoporous-silica', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physisorption', 'id': 'bcd4f7fa-8729-4acc-91a3-553a51ecf3ce', 'name': 'physisorption', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'small-angle-x-ray-scattering-saxs', 'id': '1e279138-e340-4462-a248-79f0591d35cb', 'name': 'small-angle-x-ray-scattering-saxs', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'transmission-electron-microscopy-tem', 'id': '15a03b4e-0a79-4fb8-b898-24d033f16fee', 'name': 'transmission-electron-microscopy-tem', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Häussermann, Dorothea', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3338', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:13.696937', 'metadata_modified': '2023-05-08T19:14:13.696942', 'name': 'doi-10-18419-darus-3338', 'notes': '<p>This dataset encludes all gas chromatography (GC), <sup>27</sup>Al magic angle spinning nuclear magnetic resonance spectroscopy (<sup>27</sup>Al MAS NMR), x-ray diffraction (XRD), CO<sub>2</sub> physisorption, inductively coupled plasma optical emission spectroscopy (ICP-OES) data and scanning electron microscope (SEM) images of the related publication: "Influence of the Synthesis Protocol on the Catalytic Performance of PHI-Type Zeolites for the Dehydration of Lactic Acid".</p>\n\n<p>The manuscript describes the influence of the synthesis protocol on the catalytic performance of PHI-type zeolites for the dehydration of lactic acid. Two PHI-type zeolites were synthesized with a few variations in the synthesis procedure. The catalysts were characterized and tested in the lactic acid dehydration reaction. During the catalytic reaction, a big difference in the performance was observed.</p>\n\n<p>The data used for the manuscript are sorted by the respective characterization method. The data are named according to the sample names. The raw data can be processed with the corresponding software.</p>', 'num_resources': 1, 'num_tags': 5, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Data for: Influence of the Synthesis Protocol on the Catalytic Performance of PHI-Type Zeolites for the Dehydration of Lactic Acid', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Häussermann, Dorothea'}, {'key': 'creator', 'value': 'Häussermann, Dorothea'}, {'key': 'date', 'value': '2023-02-07T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3338'}, {'key': 'metadata_modified', 'value': '2023-02-08T01:00:04'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': 'a049c9e0-e50f-4d05-a043-7d4751bb5880'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:13.698327', 'format': 'HTML', 'hash': '', 'id': '0ccec5ce-8884-41f5-a4d6-43f68819eae4', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:13.688923', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data for: Influence of the Synthesis Protocol on the Catalytic Performance of PHI-Type Zeolites for the Dehydration of Lactic Acid', 'package_id': 'doi-10-18419-darus-3338', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3338', 'url_type': None}], 'tags': [{'display_name': 'acrylic-acid', 'id': 'e621a5b6-c790-446c-924e-ef6b297f5d75', 'name': 'acrylic-acid', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'lactic-acid-dehydration', 'id': '922e7b38-7203-456a-b46a-49804ab0e773', 'name': 'lactic-acid-dehydration', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'phillipsite', 'id': '466fcef9-af8c-404d-9d49-2ff6eab84046', 'name': 'phillipsite', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'zeolite-synthesis', 'id': '3468d0c9-ac36-420b-82da-b581416e4d03', 'name': 'zeolite-synthesis', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Häußler, Max', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3337', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:12.942773', 'metadata_modified': '2023-05-08T19:14:12.942779', 'name': 'doi-10-18419-darus-3337', 'notes': 'Master thesis in the form of a JupyterBook with the title: "From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics"\n<p></p>\nJupyterBook can be accessed via: <a href="https://haeussma.github.io/masterthesis/welcome.html">https://haeussma.github.io/masterthesis/welcome.html</a>\n<p></p>\nGoal of the thesis was the development of a workflow for enzyme kinetics parameter estimation workflow, which is based on raw measurement data and utilises the EnzymeML format. Furthermore, data management was a vital aspect of the thesis. Thus this dataset contains all raw measurement data in the "data" folder, as well as the written thesis in form of a JupyterBook in the "book" folder. In summary, all data analysis as well as the written report can be reproduced.', 'num_resources': 1, 'num_tags': 4, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Häußler, Max'}, {'key': 'creator', 'value': 'Häußler, Max'}, {'key': 'date', 'value': '2023-02-02T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3337'}, {'key': 'metadata_modified', 'value': '2023-02-03T01:00:04'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '5369916d-bb12-47a7-8153-f3d5e8090a93'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:12.944238', 'format': 'HTML', 'hash': '', 'id': 'aed17388-f559-4da0-93b4-508209d23690', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:12.935061', 'mimetype': None, 'mimetype_inner': None, 'name': 'From raw data to kinetic parameters: an EnzymeML-based workflow for reproducible enzyme kinetics', 'package_id': 'doi-10-18419-darus-3337', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3337', 'url_type': None}], 'tags': [{'display_name': 'biocatalysis', 'id': 'ff1781d4-a04e-4683-8214-ae4a122bdc9b', 'name': 'biocatalysis', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'computer-and-information-science', 'id': '75b28b6d-af69-4c24-9c9e-451d429aad9b', 'name': 'computer-and-information-science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'data-management', 'id': 'e0da2a77-02b2-4555-80e4-8ceacb90d5ad', 'name': 'data-management', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Jeltsch, Albert, Bashtrykov, Pavel, Adam, Sabrina', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3334', 'isopen': False, 'language': 'English', 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:12.861674', 'metadata_modified': '2023-05-08T19:14:12.861682', 'name': 'doi-10-18419-darus-3334', 'notes': '<b>Expression and purification of DNMT1 for biochemical work</b><br>\nFull length murine DNMT1 (UniProtKB <a href="https://www.uniprot.org/uniprot/P13864">P13864</a>) was overexpressed and purified as described (Adam, et al. 2020) using the Bac-to-Bac baculovirus expression system (Invitrogen). The expression construct of the DNMT1 with mutated CXXC domain was taken from Bashtrykov, et al. (2012).<br>\n\n<b>Synthesis long DNA substrate and methylation reactions with them</b><br>\nThe sequence of the 349 bp substrate with 44 CpG sites was taken from Adam et al. 2020. It was used in unmethylated and hemimethylated form. Generation of the substrates and the methylation reaction were conducted as described (Adam, et al. 2020). In brief, for the generation of hemimethylated substrates, the unmethylated DNA was methylated in vitro by M.SssI (purified as described in Adam, et al. 2020) to introduce methylation at all CpG sites, or by M.HhaI (NEB) together with M.MspI (NEB) to introduce methylation at GCGC and CCGG sites. For the synthesis of hemimethylated substrates, the upper strand of the methylated substrate was digested with lambda exonuclease, the ss-DNA purified and finally ds hemimethylated DNA was generated by by primer extension using Phusion® HF DNA Polymerase (Thermo). Methylation reaction were conducted using mixtures of UM, fully hemimethylated and patterned substrate (total DNA concentration 200 ng in 20 µL) in methylation buffer (100 mM HEPES, 1 mM EDTA, 0.5 mM DTT, 0.1 mg mL-1 BSA, pH 7.2 with KOH) containing 1 mM AdoMet. DNMT1 concentrations and incubation times are indicated in the text. Methylation was followed by bisulfite conversion using the EZ DNA Methylation-LightningTM Kit (ZYMO RESEARCH) followed by library generation and Illumina paired-end sequencing (Novogene).<br>\n\n<b>Flanking sequence preference analysis with randomized single-site substrates</b><br>\nMethylation reactions of the randomized substrate with DNMT1 were performed similarly as described (Adam, et al. 2020; Gao, et al. 2020). Briefly, single-stranded oligonucleotides containing a methylated, hydroxymethylated or unmethylated CpG site embedded in a 10 nucleotide random context were obtained from IDT and used for generation of 67 bps long double-stranded DNA substrates by primer extension. Pools of these randomized substrates were then mixed in different combination, methylated by DNMT1 in methylation buffer (100 mM HEPES, 1 mM EDTA, 0.5 mM DTT, 0.1 mg mL-1 BSA, pH 7.2 with KOH) containing 1 mM AdoMet. DNMT1 concentrations and incubation times are indicated in the text. Methylation was followed by bisulfite conversion using the EZ DNA Methylation-LightningTM Kit (ZYMO RESEARCH) followed by library generation and Illumina paired-end sequencing (Novogene).<br>\n\n<b>Bioinformatics analysis</b><br>\nNGS data sets were bioinformatically analyzed using a local instance of the Galaxy server as described (Adam, et al. 2020; Dukatz, et al. 2020; Dukatz, et al. 2022). In brief, for the long substrate, reads were trimmed, filtered by quality, mapped against the reference sequence and demultiplexed using substrate type and experiment specific barcodes. Afterwards, methylation information was assigned and retrieved by home-made skripts. For the randomized substrate, reads were trimmed and filtered according to the expected DNA size. The original DNA sequence was then reconstituted based on the bisulfite converted upper and lower strands to investigate the average methylation state of both CpG sites and the NNCGNN flanks using home-made skripts. Methylation rates of 256 NNCGNN sequence contexts in the competitive methylation experiments with the mixed single-site substrates were determined by fitting to monoexponential reaction progress curves with variable time points with MatLab skripts as described (Adam, et al. 2022). Pearson correlation factors were calculated with Excel using the correl function.<br>\n\n<b>Structure of the deposited data</b><br>\nMethylation data of long substrates are placed in the “long DNA substrates” folder. Methylation data of short single-site substrates with randomized flanks are placed in the “single sites substrates” folder. In both folder an explanatory pdf file gives further information. Subfolders are arranged by enzyme (CXXC mutant or DNMT1 WT). Then, for each enzyme, the different substrates or substrate mixtures are provided in separate subfolders.<br>\n\n<b>References</b><br>\n<li>Adam S, Bräcker J, Klingel V, Osteresch B, Radde NE, Brockmeyer J, Bashtrykov P, Jeltsch A. Flanking sequences influence the activity of TET1 and TET2 methylcytosine dioxygenases and affect genomic 5hmC patterns. Communications Biology 5, 92 (2022)\n<li>Adam S, Anteneh H, Hornisch M, Wagner V, Lu J, Radde NE, Bashtrykov P, Song J, Jeltsch A. DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation. Nature Commun 11, 3723 (2020)\n<li>Bashtrykov P, et al. Specificity of Dnmt1 for methylation of hemimethylated CpG sites resides in its catalytic domain. Chem Biol 19, 572-578 (2012)\n<li>Dukatz M, Dittrich M, Stahl E, Adam S, de Mendoza A, Bashtrykov P, Jeltsch A. DNA methyltransferase DNMT3A forms interaction networks with the CpG site and flanking sequence elements for efficient methylation. J. Biol. Chem. 298(10), 102462 (2022)\n<li>Dukatz M, Adam S, Biswal M, Song J, Bashtrykov P, Jeltsch A. Complex DNA sequence readout mechanisms of the DNMT3B DNA methyltransferase. Nucleic Acids Res 48, 11495-11509 (2020)\n<li>Gao L, Emperle M, Guo Y, Grimm SA, Ren W, Adam S, Uryu H, Zhang ZM, Chen D, Yin J, Dukatz M, Anteneh H, Jurkowska RZ, Lu J, Wang Y, Bashtrykov P, Wade PA, Wang GG, Jeltsch A, Song J. Comprehensive Structure-Function Characterization of DNMT3B and DNMT3A Reveals Distinctive De Novo DNA Methylation Mechanisms. Nature Commun 11, 3355 (2020)\n<br><br>\n<b>Data set 1</b> contains the combined methylation rates of all 256 NNCGNN sequences in HM, OH and UM context by DNMT1, as well as their corresponding standard error of the mean (SEM) values. For details how these numbers were determined refer to the description in the corresponding publication.', 'num_resources': 1, 'num_tags': 8, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'NGS data related to Adam et al.: On the accuracy of the epigenetic copy machine - comprehensive specificity analysis of the DNMT1 DNA methyltransferase', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Jeltsch, Albert'}, {'key': 'creator', 'value': 'Jeltsch, Albert'}, {'key': 'date', 'value': '2023-04-04T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3334'}, {'key': 'metadata_modified', 'value': '2023-04-28T00:00:05'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '1d155cce-62c5-4d8f-86d7-eb3768892c4d'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:12.863643', 'format': 'HTML', 'hash': '', 'id': '51461cc1-1b40-41bc-b7f9-7f0efe0f67c5', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:12.830220', 'mimetype': None, 'mimetype_inner': None, 'name': 'NGS data related to Adam et al.: On the accuracy of the epigenetic copy machine - comprehensive specificity analysis of the DNMT1 DNA methyltransferase', 'package_id': 'doi-10-18419-darus-3334', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3334', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'dna-methylation', 'id': 'e7346e2a-6a27-4ef7-9a8a-67d86bc040c4', 'name': 'dna-methylation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'dna-methyltransferase', 'id': '535aedd5-dcf4-4470-90a5-ab689b1b456e', 'name': 'dna-methyltransferase', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'dnmt1', 'id': 'c2bc85f9-cd83-41a3-bb3d-d00f697ff0ad', 'name': 'dnmt1', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'enzyme-assay', 'id': 'f4d04af7-98e2-455a-a8ec-5ae1aab87681', 'name': 'enzyme-assay', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'enzyme-specificity', 'id': 'a9460414-cc78-4daa-aa69-952291b72087', 'name': 'enzyme-specificity', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'medicine-health-and-life-sciences', 'id': 'fb4c5813-8e73-46a1-ba71-17094769b523', 'name': 'medicine-health-and-life-sciences', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'raw-dna-sequences-extracted-from-fastq-ngs-files-bisulfite-seq-of-5mc-analysis', 'id': '926440e2-39e5-4f03-9eb2-2cc6387f2f2c', 'name': 'raw-dna-sequences-extracted-from-fastq-ngs-files-bisulfite-seq-of-5mc-analysis', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Gravelle, Simon, Beyer, David, Brito, Mariano E., Schlaich, Alexander, Holm, Christian', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3313', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:11.401243', 'metadata_modified': '2023-05-08T19:14:11.401249', 'name': 'doi-10-18419-darus-3313', 'notes': 'Simulations and data analysis scripts for the publication "Assessing the validity of NMR relaxation rates obtained from coarse-grained simulations". \nThe dataset contains two types of simulation scripts: all-atom simulation (GROMACS) and coarse-grained simulations (ESPRESSO). In both cases, the system is a polymer PEG bulk system. \nSee the <a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=180668">README file</a> for details and instructions.', 'num_resources': 1, 'num_tags': 5, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Scripts for "Assessing the validity of NMR relaxation rates obtained from coarse-grained simulations"', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Gravelle, Simon'}, {'key': 'creator', 'value': 'Gravelle, Simon'}, {'key': 'date', 'value': '2023-03-13T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3313'}, {'key': 'metadata_modified', 'value': '2023-03-14T01:00:04'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '2f03e55e-e433-4337-90a3-36952864183e'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:11.408907', 'format': 'HTML', 'hash': '', 'id': 'e4602d1a-e5b1-4566-a541-c4b751e7981c', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:11.390353', 'mimetype': None, 'mimetype_inner': None, 'name': 'Scripts for "Assessing the validity of NMR relaxation rates obtained from coarse-grained simulations"', 'package_id': 'doi-10-18419-darus-3313', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3313', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'espresso', 'id': '36617720-1516-47cc-9e47-0e4b0f281030', 'name': 'espresso', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'gromacs', 'id': '89f9c630-d2ac-459e-8624-7dbdd542d09c', 'name': 'gromacs', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'molecular-dynamics-simulation', 'id': '0040c50a-44c0-4113-b945-716272c88419', 'name': 'molecular-dynamics-simulation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physics', 'id': '820fb04d-8f9c-45ca-9a54-9054d91e527b', 'name': 'physics', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Rieg, Carolin, Dyballa, Michael', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3306', 'isopen': False, 'language': 'English', 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:11.349686', 'metadata_modified': '2023-05-08T19:14:11.349691', 'name': 'doi-10-18419-darus-3306', 'notes': 'Solid-state NMR data of the journal article mentioned under related publications from the Dyballa group can be found here. Data from collaborating groups (A2, A4, B3, C4) can be found in separate data sets.', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Replication data of Dyballa group for: "Determination of Accessibility and Spatial Distribution of Chiral Rh Diene Complexes Immobilized on SBA-15 via Phosphine‐based NMR Probe Molecules"', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Rieg, Carolin'}, {'key': 'creator', 'value': 'Rieg, Carolin'}, {'key': 'date', 'value': '2023-01-19T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3306'}, {'key': 'metadata_modified', 'value': '2023-01-20T01:00:05'}, {'key': 'relation', 'value': 'Structure [RhCl(L1)(P(Ad)2(n-Bu))]: Carolin Rieg, Manuel Kirchhof, Katrin Gugeler, Ann-Katrin Beurer, Lukas Stein, Klaus Dirnberger, Wolfgang Frey, Johanna R. Bruckner, Yvonne Traa, Johannes Kästner, Sabine Ludwigs, Sabine Laschat, Michael Dyballa, CCDC 2195463: Experimental Crystal Structure Determination, 2022, DOI: <a href="https://doi.org/10.5517/ccdc.csd.cc2cpkd1">10.5517/ccdc.csd.cc2cpkd1</a>'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': 'fb72fd3e-213a-496c-b0ed-08d2b100a312'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:11.357078', 'format': 'HTML', 'hash': '', 'id': 'cf366ce8-545d-4999-9272-0b6e556d8b79', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:11.342427', 'mimetype': None, 'mimetype_inner': None, 'name': 'Replication data of Dyballa group for: "Determination of Accessibility and Spatial Distribution of Chiral Rh Diene Complexes Immobilized on SBA-15 via Phosphine‐based NMR Probe Molecules"', 'package_id': 'doi-10-18419-darus-3306', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3306', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'experimental-data', 'id': '2468cb76-4757-4ec7-be40-8da1b05b5f1c', 'name': 'experimental-data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'heterogeneous-catalysis', 'id': '86b5272a-37ca-43c8-b338-18e1995d1ff5', 'name': 'heterogeneous-catalysis', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Zaverkin, Viktor, Holzmüller, David, Bonfirraro, Luca, Kästner, Johannes', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3299', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:10.521291', 'metadata_modified': '2023-05-08T19:14:10.521296', 'name': 'doi-10-18419-darus-3299', 'notes': 'Pre-trained and fine-tuned ANI models using the Gaussian Moments Neural Network (GM-NN) approach. Code for GM-NN implemented within the Tensorflow framework, including the respective documentation and tutorials, can be found <a href="https://gitlab.com/zaverkin_v/gmnn">on GitLab</a>. \n\nThe data represents TensorFlow v2 checkpoints and stores the metadata for the checkpoint and parameters for the model. Checkpoints can be read by the source code provided <a href="https://gitlab.com/zaverkin_v/gmnn">on GitLab</a>. A detailed description for reproducing the results and employing pre-trained and fine-tuned models during a simulation is provided <a href="https://zaverkin_v.gitlab.io/gmnn/tutorials/transfer_learning.html">in the GM-NN Documentation</a>.', 'num_resources': 1, 'num_tags': 11, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Zaverkin, Viktor'}, {'key': 'creator', 'value': 'Zaverkin, Viktor'}, {'key': 'date', 'value': '2023-02-20T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3299'}, {'key': 'metadata_modified', 'value': '2023-02-21T01:00:06'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '1e3d9f3c-6d7b-42df-904c-5fd345dece78'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:10.537321', 'format': 'HTML', 'hash': '', 'id': 'b0bddd32-f061-410a-bc09-9bac28fb08c4', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:10.507649', 'mimetype': None, 'mimetype_inner': None, 'name': 'Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials', 'package_id': 'doi-10-18419-darus-3299', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3299', 'url_type': None}], 'tags': [{'display_name': 'accurate-neural-network-engine-for-molecular-energies-ani', 'id': '0559f28e-5e33-426d-a5e8-5e615e15a542', 'name': 'accurate-neural-network-engine-for-molecular-energies-ani', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'atomistic-machine-learning', 'id': '2240e87f-ab38-4e03-b8ea-1e006b9268d3', 'name': 'atomistic-machine-learning', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'computer-and-information-science', 'id': '75b28b6d-af69-4c24-9c9e-451d429aad9b', 'name': 'computer-and-information-science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'coupled-cluster-cc-ansatz', 'id': '6a28d72d-d650-42ca-9425-259d86fd29a3', 'name': 'coupled-cluster-cc-ansatz', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'density-functional-theory-dft', 'id': '4c3b55d5-fe56-4a5c-92c9-bb32e2f961aa', 'name': 'density-functional-theory-dft', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'gaussian-moment-neural-network-gm-nn', 'id': 'cfb65332-2cf0-4494-a29d-39bb64315076', 'name': 'gaussian-moment-neural-network-gm-nn', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'gaussian-moments', 'id': 'a6446777-ff08-4690-b980-92eacae73188', 'name': 'gaussian-moments', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physics', 'id': '820fb04d-8f9c-45ca-9a54-9054d91e527b', 'name': 'physics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'potential-energy-surface', 'id': 'a312c19b-5ff6-44a5-ab5b-b2e6c6e29690', 'name': 'potential-energy-surface', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'transfer-learning', 'id': '442d604b-226d-4279-a05d-dcdd99e1ec7c', 'name': 'transfer-learning', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Kirchhof, Manuel', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3272', 'isopen': False, 'language': 'English', 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:08.707491', 'metadata_modified': '2023-05-08T19:14:08.707497', 'name': 'doi-10-18419-darus-3272', 'notes': 'In this dataset HPLC (high performance liquid chromatography) chromatograms of the products of the rhodium-catalyzed 1,2-addition and NMR spectra of all prepared catalysts and catalysis products (NMR) are included. The described 1,2-addition product is an N-tosyl amide which was formed from the reaction of triphenylboroxine with an N-tosyl imine. The catalysts are the chiral Rh norbornadiene phosphine complexes [RhCl(L1)(P(Ad)2(n-Bu))] and [RhCl(L1)(PPh3)]. Furthermore, the NMR data of phosphine complexation experiments is deposited. This data was collected to screen for suitable phosphines for the later quantification of accessible Rh diene complexes on SBA-15 via solid state NMR. Crystallographic data was published in Cambridge Structural Database (CSD) of the Cambridge Crystallographic Data Centre (CCDC) as stated under related datasets. In this dataset additional data from the crystal structure of [RhCl(L1)(P(Ad)2(n-Bu))] is included (plotted structure, CIF file, PDB file, RES file and a DAT file with tables listing all the significant measuring parameters, bond angles, bond distances and atom coordinates).', 'num_resources': 1, 'num_tags': 9, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Data of B3 group for: "Determination of Accessibility and Spatial Distribution of Chiral Rh Diene Complexes Immobilized on SBA-15 via Phosphine‑based NMR Probe Molecules"', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Kirchhof, Manuel'}, {'key': 'creator', 'value': 'Kirchhof, Manuel'}, {'key': 'date', 'value': '2022-12-13T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3272'}, {'key': 'metadata_modified', 'value': '2022-12-14T01:00:05'}, {'key': 'relation', 'value': 'Structure [RhCl(L1)(P(Ad)2(n-Bu))]: Carolin Rieg, Manuel Kirchhof, Katrin Gugeler, Ann-Katrin Beurer, Lukas Stein, Klaus Dirnberger, Wolfgang Frey, Johanna R. Bruckner, Yvonne Traa, Johannes Kästner, Sabine Ludwigs, Sabine Laschat, Michael Dyballa, CCDC 2195463: Experimental Crystal Structure Determination, 2022, DOI: <a href="https://doi.org/10.5517/ccdc.csd.cc2cpkd1">10.5517/ccdc.csd.cc2cpkd1</a>'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '2dad7840-1c40-4a26-88ec-033c72570e11'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:08.709237', 'format': 'HTML', 'hash': '', 'id': '74c7706a-4b82-4873-bef1-8d96e00bee06', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:08.693838', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data of B3 group for: "Determination of Accessibility and Spatial Distribution of Chiral Rh Diene Complexes Immobilized on SBA-15 via Phosphine‑based NMR Probe Molecules"', 'package_id': 'doi-10-18419-darus-3272', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3272', 'url_type': None}], 'tags': [{'display_name': 'asymmetric-catalysis', 'id': 'fed94913-f045-4f9f-8e39-65b81c869cea', 'name': 'asymmetric-catalysis', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'confinement', 'id': '6cb7505c-f92e-435f-a1dc-e7542d4a061a', 'name': 'confinement', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'diene-ligands', 'id': 'ad013382-9245-4667-bdc1-a436b823be13', 'name': 'diene-ligands', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'experimental-data', 'id': '2468cb76-4757-4ec7-be40-8da1b05b5f1c', 'name': 'experimental-data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'nmr-spectroscopy', 'id': 'f9a256af-c7a9-4bb2-b692-84675d928483', 'name': 'nmr-spectroscopy', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'phosphine', 'id': '8f62a337-0e73-43de-b0e5-dd46a28536fe', 'name': 'phosphine', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'probe-molecules', 'id': '835f5a10-d5c6-4918-9c3c-0ccbc6acbccf', 'name': 'probe-molecules', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'rhodium-catalysis', 'id': 'dee4bd4e-ccde-4323-b35b-d072bf744e0c', 'name': 'rhodium-catalysis', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Jeltsch, Albert, Schnee, Philipp, Saad, Mina, Weirich, Sara, Pleiss, Jürgen, Bashtrykov, Pavel', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3263', 'isopen': False, 'language': 'English', 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:08.163193', 'metadata_modified': '2023-05-08T19:14:08.163199', 'name': 'doi-10-18419-darus-3263', 'notes': 'This data collection contains additional data related to Khellaet al.: "The T1150A cancer mutant of the protein lysine methyltransferase NSD2 can introduce H3K36 trimethylation". \nThis includes <BR><ul>\n\n<li>Movie 1: Example of a successful docking of AdoMet to the NSD2 T1150A - H3K36me2 peptide complex</li>\n<li>Modelled structures of NSD2 bound to different peptides and cofactors\n<li>Source data of the results of the MD analysis</li>\n<li>MD simulations codes and analysis scripts</li>\n<li>Supplementary Tables</li>\n</ul>', 'num_resources': 1, 'num_tags': 10, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Additional data related to Khella et al.: The T1150A cancer mutant of the protein lysine methyltransferase NSD2 can introduce H3K36 trimethylation', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Jeltsch, Albert'}, {'key': 'creator', 'value': 'Jeltsch, Albert'}, {'key': 'date', 'value': '2023-03-14T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3263'}, {'key': 'metadata_modified', 'value': '2023-03-15T01:00:04'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '876f1931-c5e1-47b4-99c1-f13b48c833d4'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:08.175723', 'format': 'HTML', 'hash': '', 'id': '57219e49-91d2-4c08-a8e6-6ffc4dfd4fdd', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:08.150055', 'mimetype': None, 'mimetype_inner': None, 'name': 'Additional data related to Khella et al.: The T1150A cancer mutant of the protein lysine methyltransferase NSD2 can introduce H3K36 trimethylation', 'package_id': 'doi-10-18419-darus-3263', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3263', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'computer-and-information-science', 'id': '75b28b6d-af69-4c24-9c9e-451d429aad9b', 'name': 'computer-and-information-science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'enzyme-specificity', 'id': 'a9460414-cc78-4daa-aa69-952291b72087', 'name': 'enzyme-specificity', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'md-simulations-analysis-python-scripts', 'id': '090ccb6e-3f9f-42e3-ba28-8eb84aae62b5', 'name': 'md-simulations-analysis-python-scripts', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'md-simulations-python-scripts', 'id': 'b9739d54-7835-4e4c-8fd2-5f85460281ea', 'name': 'md-simulations-python-scripts', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'medicine-health-and-life-sciences', 'id': 'fb4c5813-8e73-46a1-ba71-17094769b523', 'name': 'medicine-health-and-life-sciences', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'molecular-models-of-protein-structures', 'id': '1a839617-bec8-4193-bae8-fc5ba2c7ebb2', 'name': 'molecular-models-of-protein-structures', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'primary-data-tables', 'id': '0bb08af2-fd1c-47c4-b7d4-2400eb49780d', 'name': 'primary-data-tables', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'protein-methyltransferases', 'id': 'ac68d376-42e5-4c1f-b3d2-5811016c074b', 'name': 'protein-methyltransferases', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'videos', 'id': '30874e95-14cd-418c-ab1b-9c0b6160021e', 'name': 'videos', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Klein, Karsten, Garkov, Dimitar, Rütschlin, Sina, Böttcher, Thomas, Schreiber, Falk', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3242', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:06.993704', 'metadata_modified': '2023-05-08T19:14:06.993710', 'name': 'doi-10-18419-darus-3242', 'notes': 'The add-on had been designed for the <a href="http:\\\\vanted.org">VANTED framework</a> and used to create QSDB Database\'s collection of clickable networks. Each network is laid out according to SBGN standards, showing quorum sensing and quorum quenching interactions between organisms and signaling molecules. This data set constitutes the source code of the add-on, developed to visualise the SBGN graphs of the QSDB Database using as input tabular aggregated data collected from existing literature.<br><br>\n\n<p><b>Paper abstract:</b> The human microbiome is largely shaped by the chemical interactions of its microbial members, which includes cross-talk via shared signals or quenching of the signalling of other species. Quorum sensing is a process that allows microbes to coordinate their behaviour in dependence of their population density and to adjust gene expression accordingly. We present the Quorum Sensing Database (QSDB), a comprehensive database of all published sensing and quenching relations between organisms and signalling molecules of the human microbiome, as well as an interactive web interface that allows browsing the database, provides graphical depictions of sensing mechanisms as Systems Biology Graphical Notation diagrams and links to other databases.<br><br>\n\n<b>Database URL:</b> QSDB (Quorum Sensing DataBase) is freely available via an interactive web interface and as a downloadable csv file at <a href="http://qsdb.org">http://qsdb.org</a>.</p>', 'num_resources': 1, 'num_tags': 9, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'QSDB - a graphical Quorum Sensing Database: VANTED add-on source code', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Garkov, Dimitar'}, {'key': 'creator', 'value': 'Klein, Karsten'}, {'key': 'date', 'value': '2022-11-21T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3242'}, {'key': 'metadata_modified', 'value': '2022-11-29T01:00:05'}, {'key': 'relation', 'value': 'The published produced data is available to access and download at: <a href="http:\\\\qsdb.org">http:\\\\qsdb.org</a>.'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '8e36537d-af4a-4146-a6d3-957026565d21'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:06.995355', 'format': 'HTML', 'hash': '', 'id': '051c0d01-9d0b-4ff2-a996-5159f2424844', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:06.981987', 'mimetype': None, 'mimetype_inner': None, 'name': 'QSDB - a graphical Quorum Sensing Database: VANTED add-on source code', 'package_id': 'doi-10-18419-darus-3242', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3242', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'computer-and-information-science', 'id': '75b28b6d-af69-4c24-9c9e-451d429aad9b', 'name': 'computer-and-information-science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'medicine-health-and-life-sciences', 'id': 'fb4c5813-8e73-46a1-ba71-17094769b523', 'name': 'medicine-health-and-life-sciences', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'quorum-quenching-microbiology', 'id': '866a0576-b399-43cf-95fb-4e4f66ca52cb', 'name': 'quorum-quenching-microbiology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'quorum-sensing-microbiology', 'id': '4bab2336-f29a-4339-8f2b-6861c9095719', 'name': 'quorum-sensing-microbiology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sbgn', 'id': '1a0ce8bf-2353-41e1-a90a-6e988685dfcc', 'name': 'sbgn', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'systems-biology', 'id': '4a3b851d-e9f3-4abc-9f33-390abbafb0e1', 'name': 'systems-biology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'systems-biology-graphical-notation', 'id': '884f8189-b82c-4ac2-bfcb-ad9caae7e7d2', 'name': 'systems-biology-graphical-notation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'web-databases', 'id': '2f4bb02f-e20d-4c23-9cb5-58bc87acbbdc', 'name': 'web-databases', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Jung, Jong Hyun, Srinivasan, Prashanth, Forslund, Axel, Grabowski, Blazej', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3239', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:06.616448', 'metadata_modified': '2023-05-08T19:14:06.616454', 'name': 'doi-10-18419-darus-3239', 'notes': 'Data for the publication High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials, npj Comput. Mater., DOI: <a href="https://doi.org/10.1038/s41524-022-00956-8">10.1038/s41524-022-00956-8</a> (2023) <br>\n<br>\nThis data set contains <br>\n- the training sets (VASP files), <br>\n- the low moment-tensor-potentials (MTPs) and high-MTPs, <br>\n- the effective quasiharmonic (QH) potentials, <br>\n- the free energies, <br>\n- and the final thermodynamic database (properties) for the four unaries: <br>\nNb bcc PBE, Ni fcc PBE, Al fcc PBE, Al fcc LDA, Mg hcp PBE, and Mg hcp LDA. (niobium, nickel, aluminum, and magnesium) <br>\n<br>\nA flowchart and step-by-step methodology are provided in the Supplementary Information of the publication, and a short method in its main text, for the reproduction of the results.', 'num_resources': 1, 'num_tags': 7, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Data for: High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Forslund, Axel'}, {'key': 'creator', 'value': 'Jung, Jong Hyun'}, {'key': 'date', 'value': '2023-01-11T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3239'}, {'key': 'metadata_modified', 'value': '2023-01-12T01:00:04'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '69de5227-337c-4d1a-bc8d-181f0164ca8b'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'groups': [{'description': '', 'display_name': 'openaire_data', 'id': 'openaire_data', 'image_display_url': '', 'name': 'openaire_data', 'title': 'openaire_data'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:06.625204', 'format': 'HTML', 'hash': '', 'id': '3149ef1f-e153-4115-92c1-73b811d9c08f', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:06.604105', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data for: High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials', 'package_id': 'doi-10-18419-darus-3239', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3239', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'density-functional-theory', 'id': '05ed3b04-b36f-438a-9fb9-739fe4c6e183', 'name': 'density-functional-theory', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'interatomic-potential', 'id': '1237d7a3-9e9d-4d50-9bf3-b63270957b67', 'name': 'interatomic-potential', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'machine-learning', 'id': 'f3349551-5743-4d6e-ae1e-df402bdb7802', 'name': 'machine-learning', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'machine-learning-potentials', 'id': '4e0219cf-ce5e-40a5-a2c0-7f36ed9f44ec', 'name': 'machine-learning-potentials', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'molecular-dynamics', 'id': '85e0efe8-2491-445f-85cf-1844339d99e6', 'name': 'molecular-dynamics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'thermodynamics', 'id': '096e67c1-f822-418c-9cd4-5902fb81c436', 'name': 'thermodynamics', 'state': 'active', 'vocabulary_id': None}], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Gravelle, Simon, Holm, Christian, Schlaich, Alexander', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3180', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:04.136953', 'metadata_modified': '2023-05-08T19:14:04.136959', 'name': 'doi-10-18419-darus-3180', 'notes': 'GROMACS molecular simulation input files for slit nanopores made of NaCl and Na2SO4 solid walls, and filled with respectively NaCl and Na2SO4 solutions. Initial configuration with a given salt concentration can be generated using the Python script ConfigurationGenerator.py, and successive GROMACS runs can be performed by running the runall.sh Bash script. See the <a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=198713">README.md</a> file.', 'num_resources': 1, 'num_tags': 7, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Molecular simulation scripts for slit nanopores', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Gravelle, Simon'}, {'key': 'creator', 'value': 'Gravelle, Simon'}, {'key': 'date', 'value': '2023-03-09T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3180'}, {'key': 'metadata_modified', 'value': '2023-03-10T01:00:06'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': 'bfa5cf13-f7a9-44b5-b9d5-eeceb194eaba'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:04.150618', 'format': 'HTML', 'hash': '', 'id': 'a6d6040a-030a-450a-a25a-320158d3bb8d', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:04.126132', 'mimetype': None, 'mimetype_inner': None, 'name': 'Molecular simulation scripts for slit nanopores', 'package_id': 'doi-10-18419-darus-3180', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3180', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'computer-and-information-science', 'id': '75b28b6d-af69-4c24-9c9e-451d429aad9b', 'name': 'computer-and-information-science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'gromacs', 'id': '89f9c630-d2ac-459e-8624-7dbdd542d09c', 'name': 'gromacs', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'molecular-dynamics-simulation', 'id': '0040c50a-44c0-4113-b945-716272c88419', 'name': 'molecular-dynamics-simulation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physics', 'id': '820fb04d-8f9c-45ca-9a54-9054d91e527b', 'name': 'physics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sodium-chloride', 'id': '493d4ff7-9454-41d8-9611-5d115f2e3cdf', 'name': 'sodium-chloride', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sodium-sulfate', 'id': '362f8323-c93c-47d8-a1ed-188d5e3cd6be', 'name': 'sodium-sulfate', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Gravelle, Simon, Holm, Christian, Schlaich, Alexander', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3179', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:04.062901', 'metadata_modified': '2023-05-08T19:14:04.062907', 'name': 'doi-10-18419-darus-3179', 'notes': 'GROMACS molecular simulation input files for bulk solutions of NaCl and Na2SO4. Initial configuration with different salt concentration can be generated using the Python script ConfigurationGenerator.py, and successive GROMACS runs can be performed by running the runall.sh Bash script.', 'num_resources': 1, 'num_tags': 7, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Molecular simulation scripts for bulk solutions', 'type': 'dataset', 'extras': [{'key': 'contributor', 'value': 'Gravelle, Simon'}, {'key': 'creator', 'value': 'Gravelle, Simon'}, {'key': 'date', 'value': '2023-03-08T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3179'}, {'key': 'metadata_modified', 'value': '2023-03-09T01:00:05'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '5c4a3f69-04a6-4ee7-8ecf-85ee4cf55520'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:04.064516', 'format': 'HTML', 'hash': '', 'id': '176a5862-f9ce-4958-b8d9-e4020e11f408', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:04.052527', 'mimetype': None, 'mimetype_inner': None, 'name': 'Molecular simulation scripts for bulk solutions', 'package_id': 'doi-10-18419-darus-3179', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3179', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'computer-and-information-science', 'id': '75b28b6d-af69-4c24-9c9e-451d429aad9b', 'name': 'computer-and-information-science', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'gromacs', 'id': '89f9c630-d2ac-459e-8624-7dbdd542d09c', 'name': 'gromacs', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'molecular-dynamics-simulation', 'id': '0040c50a-44c0-4113-b945-716272c88419', 'name': 'molecular-dynamics-simulation', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physics', 'id': '820fb04d-8f9c-45ca-9a54-9054d91e527b', 'name': 'physics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sodium-chloride', 'id': '493d4ff7-9454-41d8-9611-5d115f2e3cdf', 'name': 'sodium-chloride', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sodium-sulfate', 'id': '362f8323-c93c-47d8-a1ed-188d5e3cd6be', 'name': 'sodium-sulfate', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Gültig, Matthias, Range, Jan Peter, Schmitz, Benjamin, Pleiss, Jürgen', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3121', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:02.400027', 'metadata_modified': '2023-05-08T19:14:02.400034', 'name': 'doi-10-18419-darus-3121', 'notes': 'In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol-water and glycerol-water, by systematically studying the dependence of densities and diffusion coefficients from water content over the whole composition range and temperatures between 278.15 and 318.15 K. Experimental data was extracted manually from literature. The same parameter space was explored by comprehensive molecular dynamics simulations, whose results were directly transferred to the analysis platform. The benefit of data integration was illustrated by assessing the transferability of the force fields, which had been developed for pure compounds to different compositions and temperatures, and by analyzing the excess mixing properties as a measure of non-ideality of methanol-water and glycerol-water mixtures. The core of the data management and analysis platform is the newly developed Python library pyThermoML, which represents metadata, the parameters and the experimentally determined or simulated properties as Python data classes. \n<br></br>\nThe feasibility of a seamless data flow from data acquisition to a comprehensive data analysis was demonstrated. <a href="https://github.com/FAIRChemistry/pyThermoML">PyThermoML</a> enables interoperability and reusability of the datasets. The publication of ThermoML documents on the Dataverse installation of the University of Stuttgart (DaRUS) makes thermophysical data findable and accessible, and thus FAIR.\n<br></br>\nThe usage of pyThermoML is demonstrated in the following <a href="https://github.com/FAIRChemistry/pyThermoML/blob/master/pyThermoML_example_workflow/templateThermoML.ipynb">example workflow</a> and can be utilized to read the given ThermoML file.', 'num_resources': 1, 'num_tags': 10, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Viscosities of experimental aqueous glycerol mixtures', 'type': 'dataset', 'extras': [{'key': 'creator', 'value': 'Gültig, Matthias'}, {'key': 'date', 'value': '2022-10-28T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3121'}, {'key': 'metadata_modified', 'value': '2022-11-29T01:00:05'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': '55485897-9cf6-4aa8-8dc6-7e41da13d5f1'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:02.413805', 'format': 'HTML', 'hash': '', 'id': 'c75e3088-b106-4fc4-83dd-91e7dd720225', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:02.386029', 'mimetype': None, 'mimetype_inner': None, 'name': 'Viscosities of experimental aqueous glycerol mixtures', 'package_id': 'doi-10-18419-darus-3121', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3121', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'engineering', 'id': '3ff6cbc9-08ad-4fd1-aa1e-6676db9d1e1c', 'name': 'engineering', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'excess-properties', 'id': '4f0d3070-54f9-4e54-aa93-2ce8eefb5511', 'name': 'excess-properties', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'fair', 'id': 'f478468d-4177-45bd-910b-eb1eeec855fd', 'name': 'fair', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'fair-data-principles', 'id': '70904371-5f99-455f-af39-2ff1d5b1ea6b', 'name': 'fair-data-principles', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'liquid-mixtures', 'id': 'c6f22099-46e7-4e66-9cf9-ded2359d790f', 'name': 'liquid-mixtures', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'mathematical-sciences', 'id': 'e46bf35a-29e9-4b40-a5c8-db6a64e96d7d', 'name': 'mathematical-sciences', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physics', 'id': '820fb04d-8f9c-45ca-9a54-9054d91e527b', 'name': 'physics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'thermoml', 'id': 'c831467c-748e-4806-8359-ff9216511379', 'name': 'thermoml', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'transferability-of-force-fields', 'id': '0e4eb12c-951b-43dd-b6df-d7268d534adc', 'name': 'transferability-of-force-fields', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Gültig, Matthias, Range, Jan Peter, Schmitz, Benjamin, Pleiss, Jürgen', 'author_email': None, 'creator_user_id': '1be646ae-ab26-47b8-8835-e4b27f11961e', 'id': 'doi-10-18419-darus-3120', 'isopen': False, 'license_id': '', 'license_title': '', 'maintainer': 'DaRUS', 'maintainer_email': None, 'metadata_created': '2023-05-08T19:14:02.314569', 'metadata_modified': '2023-05-08T19:14:02.314575', 'name': 'doi-10-18419-darus-3120', 'notes': 'In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol-water and glycerol-water, by systematically studying the dependence of densities and diffusion coefficients from water content over the whole composition range and temperatures between 278.15 and 318.15 K. Experimental data was extracted manually from literature. The same parameter space was explored by comprehensive molecular dynamics simulations, whose results were directly transferred to the analysis platform. The benefit of data integration was illustrated by assessing the transferability of the force fields, which had been developed for pure compounds to different compositions and temperatures, and by analyzing the excess mixing properties as a measure of non-ideality of methanol-water and glycerol-water mixtures. The core of the data management and analysis platform is the newly developed Python library pyThermoML, which represents metadata, the parameters and the experimentally determined or simulated properties as Python data classes. \n<br></br>\nThe feasibility of a seamless data flow from data acquisition to a comprehensive data analysis was demonstrated. <a href="https://github.com/FAIRChemistry/pyThermoML">PyThermoML</a> enables interoperability and reusability of the datasets. The publication of ThermoML documents on the Dataverse installation of the University of Stuttgart (DaRUS) makes thermophysical data findable and accessible, and thus FAIR.\n<br></br>\nThe usage of pyThermoML is demonstrated in the following <a href="https://github.com/FAIRChemistry/pyThermoML/blob/master/pyThermoML_example_workflow/templateThermoML.ipynb">example workflow</a> and can be utilized to read the given ThermoML file.', 'num_resources': 1, 'num_tags': 10, 'organization': {'id': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'name': 'darus', 'title': 'DaRUS', 'type': 'repository', 'description': 'Chemistry collection from DaRUS, the data repository of the University of Stuttgart.', 'image_url': 'logoDarusKreis.png', 'created': '2023-05-03T09:01:04.791551', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '9a7d2a53-21f6-412a-afb9-a15122df0640', 'private': False, 'related_molecule': [], 'state': 'active', 'title': 'Viscosities of experimental aqueous methanol mixtures', 'type': 'dataset', 'extras': [{'key': 'creator', 'value': 'Gültig, Matthias'}, {'key': 'date', 'value': '2022-10-28T00:00:00'}, {'key': 'identifier', 'value': 'https://doi.org/10.18419/darus-3120'}, {'key': 'metadata_modified', 'value': '2022-11-29T01:00:05'}, {'key': 'set_spec', 'value': 'all'}, {'key': 'harvest_object_id', 'value': 'e7536efe-3262-4d4f-b2e8-a6e453a4fab8'}, {'key': 'harvest_source_id', 'value': '8ba5ef26-d024-46cd-8099-94f1e74e7a36'}, {'key': 'harvest_source_title', 'value': 'Darus Test Harvest'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-08T19:14:02.324898', 'format': 'HTML', 'hash': '', 'id': '71ba77db-2cba-4137-9564-8c616df766e0', 'last_modified': None, 'metadata_modified': '2023-05-08T19:14:02.301278', 'mimetype': None, 'mimetype_inner': None, 'name': 'Viscosities of experimental aqueous methanol mixtures', 'package_id': 'doi-10-18419-darus-3120', 'position': 0, 'resource_type': 'HTML', 'size': None, 'state': 'active', 'url': 'https://doi.org/10.18419/darus-3120', 'url_type': None}], 'tags': [{'display_name': 'chemistry', 'id': '20e4e978-2a22-4286-a18b-4ae22d1ffca1', 'name': 'chemistry', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'engineering', 'id': '3ff6cbc9-08ad-4fd1-aa1e-6676db9d1e1c', 'name': 'engineering', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'excess-properties', 'id': '4f0d3070-54f9-4e54-aa93-2ce8eefb5511', 'name': 'excess-properties', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'fair', 'id': 'f478468d-4177-45bd-910b-eb1eeec855fd', 'name': 'fair', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'fair-data-principles', 'id': '70904371-5f99-455f-af39-2ff1d5b1ea6b', 'name': 'fair-data-principles', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'liquid-mixtures', 'id': 'c6f22099-46e7-4e66-9cf9-ded2359d790f', 'name': 'liquid-mixtures', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'mathematical-sciences', 'id': 'e46bf35a-29e9-4b40-a5c8-db6a64e96d7d', 'name': 'mathematical-sciences', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'physics', 'id': '820fb04d-8f9c-45ca-9a54-9054d91e527b', 'name': 'physics', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'thermoml', 'id': 'c831467c-748e-4806-8359-ff9216511379', 'name': 'thermoml', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'transferability-of-force-fields', 'id': '0e4eb12c-951b-43dd-b6df-d7268d534adc', 'name': 'transferability-of-force-fields', 'state': 'active', 'vocabulary_id': None}], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}], 'sort': 'score desc, metadata_modified desc', 'search_facets': {'organization': {'title': 'organization', 'items': [{'name': 'darus', 'display_name': 'DaRUS', 'count': 135}]}, 'tags': {'title': 'tags', 'items': [{'name': 'zeolite', 'display_name': 'zeolite', 'count': 4}, {'name': 'tungsten', 'display_name': 'tungsten', 'count': 7}, {'name': 'transition-metal', 'display_name': 'transition-metal', 'count': 6}, {'name': 'transferability-of-force-fields', 'display_name': 'transferability-of-force-fields', 'count': 10}, {'name': 'thermoml-file', 'display_name': 'thermoml-file', 'count': 4}, {'name': 'thermoml', 'display_name': 'thermoml', 'count': 6}, {'name': 'sodium-chloride', 'display_name': 'sodium-chloride', 'count': 5}, {'name': 'rhodium-catalysis', 'display_name': 'rhodium-catalysis', 'count': 5}, {'name': 'porous-media', 'display_name': 'porous-media', 'count': 7}, {'name': 'physics', 'display_name': 'physics', 'count': 36}, {'name': 'n-heterocyclic-carbene', 'display_name': 'n-heterocyclic-carbene', 'count': 4}, {'name': 'molybdenum', 'display_name': 'molybdenum', 'count': 10}, {'name': 'molecular-dynamics-simulation', 'display_name': 'molecular-dynamics-simulation', 'count': 14}, {'name': 'micro-x-ray-computed-tomography-micro-xrct', 'display_name': 'micro-x-ray-computed-tomography-micro-xrct', 'count': 6}, {'name': 'metathesis', 'display_name': 'metathesis', 'count': 12}, {'name': 'metal-complex', 'display_name': 'metal-complex', 'count': 6}, {'name': 'medicine-health-and-life-sciences', 'display_name': 'medicine-health-and-life-sciences', 'count': 15}, {'name': 'mathematical-sciences', 'display_name': 'mathematical-sciences', 'count': 10}, {'name': 'magnesium-sulfate', 'display_name': 'magnesium-sulfate', 'count': 4}, {'name': 'liquid-mixtures', 'display_name': 'liquid-mixtures', 'count': 10}, {'name': 'kinetics', 'display_name': 'kinetics', 'count': 4}, {'name': 'input-files-for-molecular-dynamics-simulations-with-gromacs', 'display_name': 'input-files-for-molecular-dynamics-simulations-with-gromacs', 'count': 4}, {'name': 'image-data', 'display_name': 'image-data', 'count': 6}, {'name': 'heterogeneous-catalysis', 'display_name': 'heterogeneous-catalysis', 'count': 5}, {'name': 'gromacs', 'display_name': 'gromacs', 'count': 6}, {'name': 'fair-data-principles', 'display_name': 'fair-data-principles', 'count': 10}, {'name': 'fair', 'display_name': 'fair', 'count': 10}, {'name': 'experimental-data', 'display_name': 'experimental-data', 'count': 26}, {'name': 'excess-properties', 'display_name': 'excess-properties', 'count': 10}, {'name': 'enzymology', 'display_name': 'enzymology', 'count': 4}, {'name': 'enzymeml', 'display_name': 'enzymeml', 'count': 4}, {'name': 'enzyme-assay', 'display_name': 'enzyme-assay', 'count': 5}, {'name': 'engineering', 'display_name': 'engineering', 'count': 24}, {'name': 'earth-and-environmental-sciences', 'display_name': 'earth-and-environmental-sciences', 'count': 10}, {'name': 'dnmt3a', 'display_name': 'dnmt3a', 'count': 4}, {'name': 'dna-methyltransferase', 'display_name': 'dna-methyltransferase', 'count': 5}, {'name': 'dna-methylation', 'display_name': 'dna-methylation', 'count': 5}, {'name': 'diene-ligands', 'display_name': 'diene-ligands', 'count': 5}, {'name': 'density-functional-theory-dft', 'display_name': 'density-functional-theory-dft', 'count': 3}, {'name': 'covalent-organic-framework', 'display_name': 'covalent-organic-framework', 'count': 3}, {'name': 'confinement', 'display_name': 'confinement', 'count': 10}, {'name': 'computer-and-information-science', 'display_name': 'computer-and-information-science', 'count': 24}, {'name': 'chemistry', 'display_name': 'chemistry', 'count': 135}, {'name': 'catalysis', 'display_name': 'catalysis', 'count': 10}, {'name': 'c-c-coupling', 'display_name': 'c-c-coupling', 'count': 3}, {'name': 'biotechnology', 'display_name': 'biotechnology', 'count': 4}, {'name': 'biomineralization', 'display_name': 'biomineralization', 'count': 3}, {'name': 'asymmetric-catalysis', 'display_name': 'asymmetric-catalysis', 'count': 5}, {'name': 'alkylidene-group', 'display_name': 'alkylidene-group', 'count': 4}, {'name': 'adsorption', 'display_name': 'adsorption', 'count': 5}]}, 'res_format': {'title': 'res_format', 'items': [{'name': 'HTML', 'display_name': 'HTML', 'count': 135}]}, 'license_id': {'title': 'license_id', 'items': [{'name': '', 'display_name': '', 'count': 135}]}}}, 'search_params': None} |