424 Smith Hall
Newark, Delaware 19716
PhD | 1992 | Peking University
My research interests are in bioinformatics. I am particularly interested in developing statistical and machine learning methods that are effective, expressive and interpretable, via incorporating domain specific knowledge of biological systems.
- Jiefu Li, Jung-Youn Lee, Li Liao. A new algorithm to train hidden Markov models for biological sequences with partial labels BMC Bioinformatics (2021) 22:162
- Pakeeza Akram and Li Liao. Prediction of comorbid diseases using weighted geometric embedding of human interactome BMC Medical Genomics, 2019,12(Suppl 7):161.
- Lei Huang, Li Liao, and Cathy Wu. Completing sparse and disconnected protein-protein networks by deep learning. BMC Bioinformatics 19:103, 2018.
- Lei Huang, Li Liao, and Cathy Wu. Protein-protein interaction prediction based on multiple kernels and partial network with linear programming. BMC Systems Biology, 2016 10(Suppl 2):45.
- Colin Kern, Alvaro J. Gonzalez, Li Liao and Vijay Shanker. Predicting Interacting Residues Using Long-Distance Information and Novel Decoding in Hidden Markov Models. IEEE Transactions on NanoBioscience, 2013, 12: 158-164.
- Alvaro Gonzalez, Li Liao and Cathy Wu. Prediction of contact matrix for protein-protein interaction. Bioinformatics, 2013, 29:1018-1025.
- Roger A. Craig, Jin Lu, Jinquan Luo, Lei Shi, and Li Liao. Optimizing nucleotide sequence ensembles for combinatorial protein libraries using a genetic algorithm. Nucleic Acids Research 38(2):e10 2010.
- Roger Craig and Li Liao, Phylogenetic Tree Information Aids Supervised Learning for Predicting Protein-Protein Interaction Based on Distance Matrices. BMC Bioinformatics 2007, 8:6.
- Robel Kahsay, Guang Gao, and Li Liao, “An improved hidden Markov model for transmembrane protein detection and topology prediction and its applications to complete genomes”, Bioinformatics, vol. 21, pp. 1853-1858, 2005.
- Li Liao and William Stafford Noble, “Combining Pairwise Sequence Similarity and Support Vector Machines for Detecting Remote Protein Evolutionary and Structural Relationships”, Journal of Computational Biology, 10(2003)857-868.