Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design-Reference-Cited by-同舟云学术

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Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design

Published:2021-08 Issue: Volume:39 Page:100401
ISSN:1347-4367
Container-title:Drug Metabolism and Pharmacokinetics
language:en
Short-container-title:Drug Metabolism and Pharmacokinetics

Author:

Sasahara Katsunori,Shibata Masakazu,Sasabe Hiroyuki,Suzuki Tomoki,Takeuchi Kenji,Umehara Ken,Kashiyama Eiji

Funder

Ministry of Education, Culture, Sports, Science and Technology

Publisher

Elsevier BV

Subject

Pharmacology (medical),Pharmaceutical Science,Pharmacology

Reference38 articles.

1. How to improve R&D productivity: the pharmaceutical industry's grand challenge;Paul;Nat Rev Drug Discov,2010

2. Computational modeling of P450s for toxicity prediction;Mishra;Expet Opin Drug Metabol Toxicol,2011

3. Computational prediction of cytochrome P450 inhibition and induction;KATO;Drug Metabol Pharmacokinet,2020

4. WhichCyp: prediction of cytochromes P450 inhibition;Rostkowski;Bioinformatics,2013

5. RS-WebPredictor: a server for predicting CYP-mediated sites of metabolism on drug-like molecules;Zaretzki;Bioinformatics,2013

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1. Application of artificial intelligence in pharmaceutical development;Novel Formulations and Future Trends;2024

2. The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery;Pharmaceutics;2023-11-12

3. Explainable artificial intelligence: A taxonomy and guidelines for its application to drug discovery;WIREs Computational Molecular Science;2023-07-26

4. Artificial Intelligence Distinguishes Pathological Gait: The Analysis of Markerless Motion Capture Gait Data Acquired by an iOS Application (TDPT-GT);Sensors;2023-07-07

5. Automated machine learning approach for developing a quantitative structure–activity relationship model for cardiac steroid inhibition of Na+/K+-ATPase;Pharmacological Reports;2023-06-24

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