Author

Rui Zhao

Beijing Jiaotong University

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

Same name, identified by ORCID

Biology Disciplines

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Bioinformatics· 2 Microbiology· 2

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:contrastive learning· 1 Approach:deep learning· 1

Frequent Co-Authors

Xiangyu LiiD· 2 shared Chao LiuiD· 1 shared Congmin ZhuiD· 1 shared Feixiong Cheng· 1 shared Guangxin LuaniD· 1 shared Guangyi Liang· 1 shared Haimeng LiiD· 1 shared Han WangiD· 1 shared

Activity by Year

2016-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 10 mutual co-author links

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2 shared papersMicrobiology

Xiangyu LiORCID

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Author profile →

4 papers

Recent·Most cited

Pseudomonas aeruginosa CRISPR-Cas primes a minimal proline-codon toxin to abort anti-CRISPR phages

Rui Wang, Chao Liu, Ping Li, J Q Xu, Guangyi Liang, Yali Wu, Xinyu Jiang, Rui Zhao, Rafael Pinilla‐Redondo, Shuai Le, Guangxin Luan, Ming Li

The paper shows Pseudomonas aeruginosa uses a CRISPR-Cas system to silence a proline-codon toxin that stops phage growth, revealing a defense mechanism against anti-CRISPR phages.

bioRxiv · Jun 3, 2026 · PreprintMicrobiology

A Deep Learning Framework for Predicting Gut Microbe-Host Receptor Interactions

Haimeng Li, Rui Zhao, Congmin Zhu, Rui Jiang, Ting Chen, Xiangyu Li, Yuqing Yang

HMI-Pred predicts gut microbe-host receptor interactions using deep learning, achieving high F1-scores and validating 47% of predictions through literature.

bioRxiv · Mar 23, 2026 · PreprintMicrobiology

SpaMOAL: A spatial multi-omics graph contrastive learning method for spatial domains identification

Jinxia Wang, Yuying Huo, Rui Zhao, Y. Pan, Han Wang, Xiangyu Li

SpaMOAL identifies spatial domains by integrating spatial coordinates, histology images, and multi-omics data through graph contrastive learning, outperforming existing methods.

bioRxiv · Feb 26, 2026 · PreprintBioinformatics

A Novel Clustering Method for Patient Stratification

Hongfu Liu, Rui Zhao, Hongsheng Fang, Feixiong Cheng, Yun Fu, Yang-Yu Liu

This paper introduces an Entropy-based Consensus Clustering (ECC) method for patient stratification, showing superior performance on cancer gene expression datasets.

bioRxiv · Sep 3, 2016Bioinformatics