Professor
Department of Bioinformatics and Systems Medicine
Contact
[email protected] | 713-500-3641
W. Jim Zheng, PhD, MS, joined McWilliams School of Biomedical Informatics at UTHealth Houston, formerly UTHealth Houston School of Biomedical Informatics (SBMI) in 2013 as an associate professor and associate director of the Center for Computational Biomedicine. After receiving his M.S. in computer science from UT Dallas and his Ph.D. from UT Southwestern, when he discovered a novel enzyme mechanism [1], Dr. Zheng spent most of his career in bioinformatics research in both industrial and academic settings. In his early career, Dr. Zheng worked on bioinformatics research and development projects in industry that involved functional genomics and data management, genome annotation, comparative genomics, and gene discovery in disease-relevant genomic regions. He also developed commercial genomic databases and bioinformatics software.
Dr. Zheng's research interests focus on how to integrate, model, visualize and mine eukaryotic genome information for translational medicine. He is also pursuing novel approaches for knowledge representation. Dr. Zheng and his colleagues developed Genome3D, the first model-view framework to integrate and visualize the eukaryotic genome in three dimensions [2]. His group also developed the concept of Ontology Fingerprints—the first Gene Ontology term embedding for the distributed representation of genes computationally developed from mining the biomedical literature [3, 4]. In addition, Dr. Zheng's group is one of the first to use deep learning approaches to predict effective drug combinations [5]. He has been developing various deep-learning models for biomedical research and shared his perspectives on data science, informatics, and artificial intelligence in an article in JAMA [6]. Taking a data-driven approach, Dr. Zheng's group and his colleagues recently discovered the extensive presence of murine viral genome sequences in patient-derived xenografts (PDX). The finding raised some serious concerns about the quality control of this important platform for cancer drug development, and the paper offered some suggestions to improve the drug development process [7]. The UTHealth team, led by Dr. Zheng and Dr. Hua Xu, also achieved significant recognition by securing 2nd place in both the 2021 Large Scale Track of the DrugProt BioCreative VII competition [8] and the 2022 NIH/NCATS LitCoin Natural Language Processing Challenge [9]. Recently, Dr. Zheng’s team and collaborators leveraged the Nobel Prize-winning AI algorithm, AlphaFold, to systematically analyze the structural impact of alternative splicing. This work laid the foundation for developing a new generation of biomedical knowledge base, with artificial intelligence playing a central role in its creation [10].
Dr. Zheng also established and directs the Data Science and Informatics Core for Cancer Research (DSICCR)—a cutting-edge data science resource with faculty expertise covering high-throughput genomic data analysis, systems biology, electronic health record mining, and clinical data warehouse development. To date, DSICCR has contributed to over 100 publications. In addition, Dr. Zheng directs the Bioinformatics and High-Performance Computing Service Center - part of the Center for Clinical and Translational Sciences supported by the NIH CTSA award.
Dr. Zheng's current translational research involves the development of novel data mining methods to extract information from the biomedical literature for novel therapeutic strategies against cancer, Alzheimer's disease, and other chronic diseases. Dr. Zheng serves on the editorial board of two bioinformatics journals, and his research is currently supported by the NIH, DoD, and the Cancer Prevention and Research Institute of Texas.
"The paradigm shift from data generation to data analysis in biomedical research has created enormous opportunities for informaticians," said Zheng. "Translating biomedical discoveries to bedside practices becomes possible through informatics research."
Clinical Information Systems (CISs)