<HashMap><database>biostudies-other</database><scores/><additional><omics_type>Unknown</omics_type><volume>20</volume><submitter>Zainab Ashimiyu-Abdusalam</submitter><journal>International journal of molecular sciences</journal><pagination>E3170</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/MODEL2406030003</full_dataset_link><repository>biostudies-other</repository><additional_accession>31261723</additional_accession><pubmed_authors>Zainab Ashimiyu-Abdusalam</pubmed_authors><pubmed_authors>Miquel Duran-Frigola</pubmed_authors></additional><is_claimable>false</is_claimable><name>Chi2019 - In Silico Prediction of PAMPA Effective Permeability Using a Two-QSAR Approach</name><description>&lt;p>The authors provide a dataset of 200 small molecules and their experimentally measured permeability in a PAMPA assay. Using this data, we have trained a model that predicts the logarithm of the effective permeability coefficient.&lt;/p>&lt;p>&lt;normal>Model Type:&lt;/normal> Predictive machine learning model.&lt;br>&lt;normal>Model Relevance:&lt;/normal> Predicts pampa-permeability.&lt;br>&lt;normal>Model Encoded by:&lt;/normal>  Miquel Duran Frigola (Ersilia)&lt;br>&lt;normal>Metadata Submitted in BioModels by:&lt;/normal> Zainab Ashimiyu-Abdusalam&lt;/p>&lt;p>Implementation of this model code by &lt;a href="https://ersilia.io/">Ersilia&lt;/a> is available here: &lt;br>&lt;a href="https://github.com/ersilia-os/eos97yu">https://github.com/ersilia-os/eos97yu&lt;/a>&lt;/p>&lt;img src="https://www.ebi.ac.uk/biomodels/static-assets/images/ersilia-logo.png" alt="Ersilia Logo" width="150"></description><dates><release>2024-06-03T00:00:00Z</release><modification>2025-07-14T17:01:59.926Z</modification><creation>2025-03-31T13:26:21.942Z</creation></dates><accession>MODEL2406030003</accession><cross_references><bao>0010072</bao><bao>0000009</bao><bao>0002305</bao><stato>STATO:0000571</stato><stato>STATO:0000237</stato><pubmed>31261723</pubmed><ncit>NCIT:C53237</ncit><ncit>NCIT:C78542</ncit><ncit>NCIT:C65172</ncit><ncit>NCIT:C16309</ncit><edam>topic_3336</edam><edam>topic_0154</edam><edam>topic_3474</edam><edam>data_1497</edam><cheminf>CHEMINF:000018</cheminf><obi>OBI_0200032</obi><pato>PATO:0001578</pato><pato>PATO:0001577</pato><pato>PATO:0000970</pato><mi>MI:2045</mi><unknown>#app1-ijms-20-03170</unknown><unknown>eos97yu</unknown></cross_references></HashMap>