Software documentation Open Access
Haralambos Sarimveis
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The Jaqpot 5 GUI directs the model developers to further document their models in a way that can be easily understood and used by end-users with little or no experience on machine learning and statistical analysis. The GUI also allows the end-users to apply the models on their own data for validation and/or prediction purposes and the results are collected and visualised in automatically generated tables, graphs and reports. All major machine learning and statistical data-driven algorithms are supported in Jaqpot 5, by integrating popular libraries such as the Python Scikit-learn and the R Caret libraries. Jaqpot 5 has been designed as a generic modelling and machine learning web platform, but particular emphasis is given on serving the needs of the chemo/bio/nano/pharma/ communities by integrating QSAR, biokinetics, dose-response and read-across models. Jaqpot 5 has been developed by the <a href=\"https://www.chemeng.ntua.gr/labs/control_lab/index.html\">Unit of Process Control and Informatics</a> in the School of Chemical Engineering at the National Technical University of Athens.</p>\n\n<p> </p>\n\n<p>This document provides a tutorial for simulating biodistribution scenarios using custom PBPK models that have been deployed on Jaqpot5. The resource has been made available at <a href=\"https://app.jaqpot.org/\">https://app.jaqpot.org/</a>.</p>", "contributors": [ { "orcid": "0000-0002-8607-9965", "affiliation": "School of Chemical Engineering", "type": "ContactPerson", "name": "Haralambos Sarimveis" }, { "affiliation": "School of Chemical Engineering", "type": "ContactPerson", "name": "Pantelis Karatzas" }, { "orcid": "0000-0002-0628-8434", "affiliation": "School of Chemical Engineering", "type": "ContactPerson", "name": "Philip Doganis" } ], "title": "Jaqpot 5: How to simulate biodistribution scenarios using custom PBPK models", "license": { "id": "CC-BY-4.0" }, "relations": { "version": [ { "count": 1, "index": 0, "parent": { "pid_type": "recid", "pid_value": "3610181" }, "is_last": true, "last_child": { "pid_type": "recid", "pid_value": "3610182" } } ] }, "communities": [ { "id": "nanocommons" } ], "grants": [ { "code": "731032", "links": { "self": "https://zenodo.org/api/grants/10.13039/501100000780::731032" }, "title": "The European Nanotechnology Community Informatics Platform: Bridging data and disciplinary gaps for industry and regulators (NanoCommons)", "acronym": "NanoCommons", "program": "H2020", "funder": { "doi": "10.13039/501100000780", "acronyms": [], "name": "European Commission", "links": { "self": "https://zenodo.org/api/funders/10.13039/501100000780" } } }, { "code": "731075", "links": { "self": "https://zenodo.org/api/grants/10.13039/501100000780::731075" }, "title": "OpenRiskNet: Open e-Infrastructure to Support Data Sharing, Knowledge Integration and in silico Analysis and Modelling in Risk Assessment", "acronym": "OpenRiskNet", "program": "H2020", "funder": { "doi": "10.13039/501100000780", "acronyms": [], "name": "European Commission", "links": { "self": "https://zenodo.org/api/funders/10.13039/501100000780" } } } ], "keywords": [ "Machine learning", "Biokinetics", "ChemInformatics", "NanoInformatics" ], "publication_date": "2020-01-16", "creators": [ { "affiliation": "School of Chemical Engineering", "name": "Haralambos Sarimveis" } ], "access_right": "open", "resource_type": { "subtype": "softwaredocumentation", "type": "publication", "title": "Software documentation" }, "related_identifiers": [ { "scheme": "doi", "identifier": "10.5281/zenodo.3610181", "relation": "isVersionOf" } ] } }
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Data volume | 218.6 MB | 218.6 MB |
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