Author

Zhangyang Wang

Texas A&M UniversityORCID 0000-0002-2050-5693Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Assay:protein sequence· 2 Assay:metagenomics· 1

Frequent Co-Authors

Di Jia WuiD· 2 shared Mostafa KarimiiD· 2 shared Yang SheniD· 2 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersBioinformatics

Di Jia WuORCID

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2 papers

Recent·Most cited

Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts

Mostafa Karimi, Di Jia Wu, Zhangyang Wang, Yang Shen

This paper develops interpretable deep learning models for structure-free compound-protein affinity prediction and contact mapping, showing improved interpretability and performance.

Journal of Chemical Information and Modeling · Dec 21, 2020Peer-reviewedBioinformatics

DeepAffinity: Interpretable Deep Learning of Compound Protein Affinity through Unified Recurrent and Convolutional Neural Networks

Mostafa Karimi, Di Jia Wu, Zhangyang Wang, Yang Shen

DeepAffinity predicts compound-protein affinity using a semi-supervised deep learning model combining recurrent and convolutional networks, achieving high accuracy and interpretability.

Bioinformatics · Feb 15, 2019Peer-reviewedBioinformatics