Journal of Molecular Biology

Mo Liu is a Professor at the Sino-French Hoffman Institute, Guangzhou Medical University, specializing in bioinformatics research with a strong focus on multi-omics analysis, cancer genomics, and algorithm development. He previously worked as a Senior Bioinformatics Scientist at BeOne Medicine and as a Research Fellow at Duke-NUS Medical School. His career spans both academia and industry, with extensive contributions to cancer genomics, mutational signature discovery, and the application of AI in biomarker analysis.

• Cancer Genomics
• Multi-omics Data Integration
• Machine Learning & Artificial Intelligence in Biomedical Research
• Bioinformatics Algorithm Development

1. Principal Investigator of multiple national and international grants (NSFC Young Scientists Fund, Ministry of Science and Technology Key R&D Program, Guangzhou Science Bureau Projects).

2. Developer of mSigHdp R package for mutational signature discovery.

3. Contributor to China Liver Cancer Atlas, the most comprehensive liver cancer database in China.

4. Active collaborator with leading research groups across China and internationally (e.g., Peking University, Chinese Academy of Engineering).

1. Chen L., Zhang C., Xue R., Liu M., Rozen S., Wang H. (2024). Deep Whole Genome Analysis of 494 Hepatocellular Carcinoma. Nature. (IF: 64.8)

2. Yang Y., Liu M., Zhai W. (2025). An expanding universe of mutational signatures and its rapid evolution in single-stranded RNA viruses. Molecular Biology and Evolution, 42(2): msaf009. (IF: 11.0)

3. Boot A., Liu M., et al. (2022). Recurrent mutations in topoisomerase IIα cause a previously undescribed mutator phenotype in human cancers. PNAS, 119(4): e2114024119. (IF: 12.8)

4. Liu M., Wu Y., Rozen S. (2023). mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery. NAR Genomics and Bioinformatics, 5(1): lqad005. (IF: 5.0)

5. Liu M., Boot A., Ng WTA., Rozen S. (2021). Mutational Processes in Cancer Preferentially Affect Binding of Particular Transcription Factors. Scientific Reports, 11, 3339. (IF: 5.0)