Dr. Liang Xue | Computational Biology | Best Researcher Award

Biopharmaceutical Director, Purdue University, United States

Dr. Liang Xue, PhD is a highly accomplished biopharmaceutical and bioinformatics leader with extensive experience in integrating multi-omics research, artificial intelligence, and strategic project management to drive innovation in therapeutic discovery. Drawing on a Ph.D. in Analytical Biochemistry from Purdue University, a postdoctoral fellowship at the California Institute of Technology, and a Master’s degree in Data Science from Northeastern University, Dr. Liang Xue has cultivated a rare blend of wet-lab expertise, computational biology proficiency, and AI/ML model development for complex biomedical datasets. Professionally, Dr. Liang Xue has advanced through successive research and leadership positions, from Scientist roles at Celgene to Principal, Senior Principal, and now Director of Bioinformatics at a leading global pharmaceutical organization in Cambridge, Massachusetts, where she supervises multidisciplinary teams, secures external research funding, and builds international collaborations with universities and start-ups to modernize proteomics infrastructure. Her research interests span proteogenomics, phosphoproteomics, biomarker discovery, protein degradation pathways, and AI-enabled therapeutic target identification, with a strong emphasis on developing reproducible, scalable pipelines for big data generation and analysis. Dr. Liang Xue’s research skills include advanced mass spectrometry, spectrum processing, kinase-substrate mapping, CRISPR-based drug screening, and cloud-based bioinformatics workflows, as well as designing AI/ML methodologies for high-dimensional data interpretation. She has published widely in high-impact, peer-reviewed journals h-indexed 15, Citations by 1,715 documents in Scopus and Web of Science, contributing to fields such as proteomics, systems biology, and translational pharmacology, and her work has been cited extensively, reflecting significant influence on both academic and industrial research communities.

Profile: GOOGLE SCHOLAR |SCOPUS

Featured Publications

Xue, L., Tiwary, S., Bordyuh, M., Stanton, R. (2025). CoSpred: Machine learning workflow to predict tandem mass spectrum in proteomics. Proteomics, 25(15), 27–41. Cited by 1

Staniak, M., Huang, T., Figueroa-Navedo, A. M., Kohler, D., Choi, M., Hinkle, T., … (2025). Relative quantification of proteins and post-translational modifications in proteomic experiments with shared peptides: a weight-based approach. Bioinformatics, 41(3), btaf046.

Xue, L., van Kalken, D., James, E. M., Giammo, G., Labenski, M. T., Cantin, S., … (2024). A probe-free occupancy assay to assess a targeted covalent inhibitor of receptor tyrosine-protein kinase erbB-2. ACS Pharmacology & Translational Science, 7(8), 2507–2515.

Jelinsky, S., Lee, I., Monetti, M., Breitkopf, S., Martz, F., Kongala, R., Culver, J., … (2024). Proteomic differences in colonic epithelial cells in ulcerative colitis have an epigenetic basis. Gastro Hep Advances, 3(6), 830–841. Cited by 2

Ray, A., Wen, J., Yammine, L., Culver, J., Parida, I. S., Garren, J., Xue, L., Hales, K., … (2023). Regulated dynamic subcellular GLUT4 localization revealed by proximal proteome mapping in human muscle cells. Journal of Cell Science, 136(23), jcs261454. Cited by 13