Author

Zhaofeng Ye

Tencent (China)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:differential expression· 2 Research Focus:drug response / drug discovery· 2 Organism:human· 2 Assay:protein sequence· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Assay:CITE-seq· 1

Frequent Co-Authors

Jiezhong QiuiD· 2 shared Amanda Katherina HerbrandiD· 1 shared Bo CheniD· 1 shared Carlos Jaime CamachoiD· 1 shared Chang‐Yu HsiehiD· 1 shared Danyu LiiD· 1 shared Evelyn Süß· 1 shared Jason E. GestwickiiD· 1 shared

Activity by Year

2018-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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2 shared papersBioinformatics

Jiezhong QiuORCID

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Author profile →

4 papers

Recent·Most cited

MdrDB: Mutation-induced drug resistance DataBase

Ziyi Yang, Zhaofeng Ye, Jiezhong Qiu, Rongjun Feng, Danyu Li, Chang‐Yu Hsieh, Jonathan Allcock, Shengyu Zhang

MdrDB is a database of mutation-induced drug resistance information, combining experimental data and computational predictions to study protein-ligand binding changes.

Communications Chemistry · Jun 14, 2023Peer-reviewedBioinformatics

Improve the Protein Complex Prediction with Protein Language Models

Bo Chen, Ziwei Xie, Jiezhong Qiu, Zhaofeng Ye, Jinbo Xu, Jie Tang

This paper introduces ESMPair, a method using protein language models to improve interolog identification, leading to better protein complex structure prediction than AlphaFold-Multimer.

bioRxiv · Sep 15, 2022 · PreprintBioinformatics

MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data

Zhenyi Wang, Yanjie Zhong, Zhaofeng Ye, Lang Zeng, Yang Chen, Minglei Shi, Minping Qian, Michael Q. Zhang

MarkovHC is a clustering algorithm that identifies cell types, trajectories, and critical points in single-cell omics data by reconstructing a pseudo-energy landscape based on metastability theory.

bioRxiv · Nov 4, 2020 · PreprintBioinformatics

Predicting protein targets for drug-like compounds using transcriptomics

Nicolas A Pabon, Yan Xia, Samuel K. Estabrooks, Zhaofeng Ye, Amanda Katherina Herbrand, Evelyn Süß, Ricardo M. Biondi, Victoria A. Assimon, Jason E. Gestwicki, Jeffrey L. Brodsky, Carlos Jaime Camacho, Ziv Bar‐Joseph

The paper develops a pipeline to predict protein targets for drug-like compounds using transcriptomics and machine learning, achieving 26% top-10 accuracy on FDA-approved drugs.

PLoS Computational Biology · Dec 7, 2018Peer-reviewedGenomics