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Haralambos Sarimveis
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Machine learning</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Biokinetics</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">ChemInformatics</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">NanoInformatics</subfield> </datafield> <controlfield tag="005">20200120172736.0</controlfield> <controlfield tag="001">3610182</controlfield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">School of Chemical Engineering</subfield> <subfield code="0">(orcid)0000-0002-8607-9965</subfield> <subfield code="4">prc</subfield> <subfield code="a">Haralambos Sarimveis</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">School of Chemical Engineering</subfield> <subfield code="4">prc</subfield> <subfield code="a">Pantelis Karatzas</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">School of Chemical Engineering</subfield> <subfield code="0">(orcid)0000-0002-0628-8434</subfield> <subfield code="4">prc</subfield> <subfield code="a">Philip Doganis</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">1278256</subfield> <subfield code="z">md5:9f1d0470a191c793521af49947d2fb41</subfield> <subfield code="u">https://zenodo.org/record/3610182/files/JPQ5_UI_TUTORIAL_NTUA_PBPK.pdf</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2020-01-16</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">openaire</subfield> <subfield code="p">user-nanocommons</subfield> <subfield code="o">oai:zenodo.org:3610182</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="u">School of Chemical Engineering</subfield> <subfield code="a">Haralambos Sarimveis</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Jaqpot 5: How to simulate biodistribution scenarios using custom PBPK models</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">user-nanocommons</subfield> </datafield> <datafield tag="536" ind1=" " ind2=" "> <subfield code="c">731032</subfield> <subfield code="a">The European Nanotechnology Community Informatics Platform: Bridging data and disciplinary gaps for industry and regulators (NanoCommons)</subfield> </datafield> <datafield tag="536" ind1=" " ind2=" "> <subfield code="c">731075</subfield> <subfield code="a">OpenRiskNet: Open e-Infrastructure to Support Data Sharing, Knowledge Integration and in silico Analysis and Modelling in Risk Assessment</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield> <subfield code="a">Creative Commons Attribution 4.0 International</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><p>Jaqpot 5 is a user-friendly web-based e-infrastructure that allows model developers to deploy their predictive models and share them through the web. The Jaqpot 5 GUI&nbsp; 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.&nbsp;&nbsp; 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,&nbsp; 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.&nbsp; 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> <p>&nbsp;</p> <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></subfield> </datafield> <datafield tag="773" ind1=" " ind2=" "> <subfield code="n">doi</subfield> <subfield code="i">isVersionOf</subfield> <subfield code="a">10.5281/zenodo.3610181</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.5281/zenodo.3610182</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">softwaredocumentation</subfield> </datafield> </record>
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