Estimation of Pharmacological Activity by Combining Molecular Fingerprints and Skeletal Formula Images
Author:
Affiliation:
1. Graduate School of Digital Contents, Digital Hollywood University,Tokyo,Japan
2. School of Digital Contents, Musashino University / Digital Hollywood University,Department of Data Science / Graduate,Tokyo,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10123436/10123450/10123570.pdf?arnumber=10123570
Reference25 articles.
1. Molecular image-convolutional neural network (CNN) assisted QSAR models for predicting contaminant reactivity toward OH radicals: Transfer learning, data augmentation and model interpretation
2. Interpretation of compound activity predictions from complex machine learning models using local approximations and Shapley values;rodrígucz-pérczkaqucl;J Med Chem,2020
3. Protein-ligand binding prediction using deep learning;yoda;Dai 81 kai zenkoku taikai kouen ronbunsyu (The 81st National Convention Lecture Paper Collection) Information Processing Society of Japan,2019
4. Virtual screening of dipeptidyl peptidase-4 inhibitors using quantitative structure–activity relationship-based artificial intelligence and molecular docking of hit compounds
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