Jake Chen, Ph.D., Chief Bioinformatics Officer of the UAB Department of Biomedical Informatics and Data Science, served as the session chair of Representational Learning in Genome Biology and Precision Medicine during the Great Lakes Bioinformatics (GLBIO) Conference in Montreal, Quebec, Canada.

The conference was held from May 15-18 at McGill University and was organized by the Great Lakes Bioinformatics Consortium to host a forum to discuss research findings and methods. GLBIO’s primary goal was to provide a platform of establishing networking opportunities and joint relationships as it relates to computational approaches to biology.

Dr. Chen’s session aimed to bring various perspectives from researchers and trainees to establish discussions reconsidering how to use artificial intelligence/machine learning (AI/ML) power more efficiently for a better disease biology understanding. Some of the topics discussed included: 

• Characterizing and reducing data noises from different omics platforms for AI/ML applications
• Identifying data pre-processing techniques that will assist in normalizing, combining, and comparing multi-omics results from different experimental conditions
• Identifying ways to balance knowledge-guided and knowledge-agnostic approaches in the development of AI/ML predictive models
• Inferring the cellular states and their dynamics, along with multi-scale causal network knowledge using AI/ML

Speakers from Dr. Chen’s session included:

•       Huanmei Wu, Ph.D., Professor and Chair, Health Services Administration and Policy, Temple University
•       Zhaohui Qin, Ph.D., Professor of Biostatistics and Bioinformatics, Emory University
•       Brandon Xia, Ph.D., Department of Bioengineering, McGill University
•       Qianqian Song, Ph.D., Assistant Professor of Cancer Biology, Wake Forest University
•       Tae Hyun Hwang, Ph.D., Florida Department of Health Cancer Chair Professor, Mayo Clinic Cancer Center