Author

Zihan Luo

Huazhong University of Science and TechnologyORCID 0000-0002-7142-448XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3 Cell Biology· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Assay:proteomics· 2 Research Focus:variant effect prediction· 2 Assay:whole-genome sequencing· 2 Organism:C. elegans· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

Chee Keong KwohiD· 3 shared Rui YiniD· 3 shared Pei ZhuangiD· 2 shared Zhuoyi LiniD· 2 shared Bin QiiD· 1 shared Jiahao ZhaoiD· 1 shared Kenan ZhangiD· 1 shared Lang WangiD· 1 shared

Activity by Year

2020-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersBioinformatics

Chee Keong KwohORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Microbial Tryptophan Metabolism Activates Host Lysosomal Activity to Facilitate Lipid Breakdown and Ameliorate Hepatic Steatosis

Kenan Zhang, Zihan Luo, Yan Li, Yan Chen, Lang Wang, Yanan Liu, Ruizhi Yang, Qian Li, Jiahao Zhao, Bin Qi, Zhao Shan

This study identifies how bacterial tryptophan metabolism activates lysosomal function to promote lipid breakdown and reduce hepatic steatosis in both C. elegans and mice.

bioRxiv · Jun 28, 2025 · PreprintCell Biology

ViPal: A Framework for Virulence Prediction of Influenza Viruses with Prior Viral Knowledge Using Genomic Sequences

Rui Yin, Zihan Luo, Pei Zhuang, Min Zeng, Min Li, Zhuoyi Lin, Chee Keong Kwoh

ViPal improves influenza virulence prediction by integrating prior viral knowledge into machine learning models using genomic sequences.

Journal of Biomedical Informatics · May 11, 2023Peer-reviewedBioinformatics

VirPreNet: A weighted ensemble convolutional neural network for the virulence prediction of influenza A virus using all 8 segments

Rui Yin, Zihan Luo, Pei Zhuang, Zhuoyi Lin, Chee Keong Kwoh

VirPreNet predicts influenza A virus virulence using all 8 viral segments with a weighted ensemble CNN, achieving state-of-the-art performance and highlighting the importance of PB2 and HA segments.

Bioinformatics · Oct 6, 2020Peer-reviewedBioinformatics

Alignment-free machine learning approaches for the lethality prediction of potential novel human-adapted coronavirus using genomic nucleotide

Rui Yin, Zihan Luo, Chee Keong Kwoh

This study develops alignment-free machine learning models to predict the lethality of novel human coronaviruses using genomic nucleotide sequences, achieving 96.7% accuracy on existing strains.

bioRxiv · Jul 15, 2020 · PreprintBioinformatics