Author

Liangren Zhang

Peking UniversityORCID 0000-0002-7362-9497Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:benchmarking· 2 Research Focus:database / resource· 1 Research Focus:drug response / drug discovery· 1 Organism:fungi (other)· 1 Research Focus:gene regulatory network inference· 1 Research Focus:protein structure prediction· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Jie XiaiD· 2 shared Song WuiD· 2 shared Aili FaniD· 1 shared Bochao YangiD· 1 shared Chenliang QianiD· 1 shared Dong LiuiD· 1 shared Dongmei WangiD· 1 shared Fan YangiD· 1 shared

Activity by Year

2024-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersPharmacology & Toxicology

Jie XiaORCID

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3 papers

Recent·Most cited

Geometry-based BERT: an experimentally validated deep learning model for molecular property prediction in drug discovery

Xiang Zhang, Chenliang Qian, Bochao Yang, Hongwei Jin, Song Wu, Jie Xia, Fan Yang, Liangren Zhang

This paper introduces GEO-BERT, a deep learning model for molecular property prediction, validated through benchmarking and prospective studies on DYRK1A inhibitors.

Journal of Pharmaceutical Analysis · Oct 10, 2025Peer-reviewedPharmacology & Toxicology

f-BGM enables fungi-specific genome mining in high accuracy and interpretability

Yiran Zhou, Dong Liu, Zequan Huang, Xingsi Xie, Wenhan Lin, Liangren Zhang, Aili Fan, Zhenming Liu

f-BGM is a deep learning framework for fungal genome mining that outperforms existing methods in BGC detection and provides interpretability for enzyme identification and domain partnerships.

bioRxiv · Jul 8, 2025 · PreprintBioinformatics

Deep Reinforcement Learning Enables Better Bias Control in Benchmark for Virtual Screening

Tao Shen, Shan Li, Xiang Simon Wang, Dongmei Wang, Song Wu, Jie Xia, Liangren Zhang

The paper introduces a new benchmark, MUBDsyn, for virtual screening that uses deep reinforcement learning to control biases, showing improved performance over existing benchmarks.

Computers in Biology and Medicine · Feb 15, 2024Peer-reviewedBioinformatics