Chao Hou

PhD of Bioinformatics

Columbia University

Biography

I am a computational biologist developing AI models to understand how protein sequences, conformational dynamics, and interactions give rise to biological function. My long-term goal is to help build predictive in silico models of biology.

I am currently a postdoctoral researcher with Yufeng Shen at Columbia University, where I study protein fitness landscapes from evolutionary and biophysical perspectives, with a particular focus on protein language models. I received my Ph.D. in Biomedical Informatics from Peking University, where I was advised by Tingting Li. During my doctoral research, I studied protein degradation and phase separation.

I was born in Zhucheng, Shandong, China (Chinese name: 侯超). Outside of research, I enjoy basketball, photography, travel, and exploring food.

Updated: Sep. 2026

Interests

AI-based biomolecule modeling from first principles: sequence → structure ensemble → function / fitness → evolution
AI-based variant-effect modeling for precision medicine and protein design
AI-based TCR-peptide-MHC modeling for personalized cancer vaccine design
Biomolecular interaction and regulation in specific cellular context

Education

Postdoc, 2023.09-
Columbia University
PhD of Biomedical Informatics, 2020.09-2023.07
Peking University
Bachelor of Medicine and Economics, 2015.09-2020.07
Peking University

Projects

Main Publications

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Chao Hou, Di Liu, Yufeng Shen (2026). Unsupervised Discovery of Functional Sequence Patterns from Protein Language Model with MotifAE. Nature Communications.

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Chao Hou, Di Liu, Aziz Zafar, Yufeng Shen (2026). Understanding Language Model Scaling for Protein Fitness Prediction. Nature Computational Science.

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Chao Hou, Haiqing Zhao, Yufeng Shen (2026). Protein language models trained on biophysical dynamics inform mutation effects. Proc Natl Acad Sci U S A.

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Peiyu Zhu, Chao Hou, Manlin Liu, Taoyu Chen, Tingting Li, Likun Wang (2023). Investigating phase separation properties of chromatin-associated proteins using gradient elution of 1,6-hexanediol. BMC Genomics.

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Chao Hou, Xinxin Wang, Haotai Xie, Taoyu Chen, Peiyu Zhu, Xiaofeng Xu, Kaiqiang You, Tingting Li (2023). PhaSepDB in 2022: annotating phase separation-related proteins with droplet states, co-phase separation partners and other experimental information. Nucleic Acids Research.

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Chao Hou, Yuxuan Li, Mengyao Wang, Hong Wu, Tingting Li (2022). Systematic prediction of degrons and E3 ubiquitin ligase binding via deep learning. BMC Biology.

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Zhaoming Chen, Chao Hou, Liang Wang, Chunyu Yu, Taoyu Chen, Boyan Shen, Yaoyao Hou, Pilong Li, Tingting Li (2022). Screening membraneless organelle participants with machine-learning models that integrate multimodal features. Proc Natl Acad Sci U S A.

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Peng Han, Chao Hou, Xi Zheng, Lulu Cao, Xiaomeng Shi, Xiaohui Zhang, Hua Ye, Hudan Pan, Liang Liu, Tingting Li, Fanlei Hu, Zhanguo Li (2022). Serum Antigenome Profiling Reveals Diagnostic Models for Rheumatoid Arthritis. Frontiers in Immunology.

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Chao Hou, Haotai Xie, Yang Fu, Yao Ma, Tingting Li (2021). MloDisDB: a manually curated database of the relations between membraneless organelles and diseases. Briefings in Bioinformatics.

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