Bioinformatics and Computational Biology (BCB 2026)
Modern biotechnologies generate data at an unprecedented scale and resolution, but translating these data into mechanistic insight and clinical impact remains a defining challenge of the life sciences. The Bioinformatics and Computational Biology (BCB 2026) session is a continuing effort of gathering researchers, students, and industry practitioners to share methodological advances, applications, and open problems at the interface of computer science, statistics, and biology. The session welcomes original research, methodological contributions, applied case studies, and review or position papers.
Topics of interest
- Artificial Intelligence in Bioinformatics and Computational Biology
- Health Care Informatics
- Multi-omics Data Integration
- Genome, Sequence, & Population Analysis
- Single-cell & Spatial Transcriptomics Data Analysis
- Structural Bioinformatics & Drug Discovery
- Clinical Informatics & Information Systems
- Personalized Medicine/Pharmacogenomics
Submission Guidelines
https://kse2026.kse-conferences.org/call-for-papers/
Session Organizers
Tin Nguyen
Professor, Department of Industrial and Systems Engineering, Wayne State University, tin@wayne.edu
Tin Nguyen is a Professor in the Department of Industrial and Systems Engineering at Wayne State University. Dr. Nguyen received his M.Sc. and B.Sc. in Computer Science from Eotvos Lorand University (Hungary) in 2008, and his Ph.D. in Computer Science from Wayne State University in 2017. His research interests include artificial intelligence, machine learning, and data mining techniques applied to bioinformatics and computational biology. Specifically, his research laboratory focuses on developing methods and software for multi-omics data integration, biological network analysis, and single-cell data analysis. Thus far his research laboratory has published over 50 peer-reviewed articles in respected venues such as Nature Communications, Genome Research, Genome Biology, Proceedings of the IEEE, Nucleic Acids Research, Briefings in Bioinformatics, and Bioinformatics. More information can be found at: https://tinnguyen-lab.com/home
Dang Hung Tran
Associate Professor, School of Information and Communications Technology, Hanoi University of Industry, hungtd@haui.edu.vn
Dang Hung Tran is an Associate Professor in the School of Information and Communications Technology at Hanoi University of Industry (HaUI) and the former Dean of the Faculty of Information Technology at Hanoi National University of Education. He has served as a Principal Investigator for numerous high-profile research projects funded by national foundations. Dr. Tran received his Ph.D. in Computer Science from the Japan Advanced Institute of Science and Technology (JAIST) in 2009. With over 20 years of experience in both academia and administration, he is recognized as a leading expert in the integration of artificial intelligence into educational and biological systems in Vietnam. Dr. Tran’s research interests lie at the intersection of artificial intelligence, data mining, and graph representation learning, specifically applied to bioinformatics and computational biology. His research laboratory focuses on developing sophisticated machine learning models for biological network analysis, discovering interactions between non-coding RNAs and diseases, and building predictive frameworks for complex biological data.
Nam Sy Vo
Director, Genomic Medicine Division, VinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam, nam.vs@vinuni.edu.vn
Nam Sy Vo is Director of Genomic Medicine Division at VinUni Big Data Research Institute, VinUniversity, and Chief Scientist, CTO & Co-Founder at GeneStory JSC. Previously, he worked as a Senior Bioinformatics Scientist at The University of Chicago after training as a Postdoctoral Fellow at The University of Texas MD Anderson Cancer Center and obtaining a PhD in Computer Science from The University of Memphis, all in the USA. Dr. Vo’s research interests focus on analysis and interpretation of large-scale biomedical data. In general, he is interested in applying data science and machine learning in computational biology and medicine. Dr. Vo is currently leading the 1000 Vietnamese Genomes Project (VN1K) and various projects towards understanding disease risk and adverse drug reaction in the Vietnamese population. He is also building several platforms for managing, analyzing, and sharing large-scale biomedical datasets. His work has been applied to analyzing the world’s largest genomic datasets, such as The Cancer Genome Atlas (TCGA), and published in prestigious journals such as Immunity (Cell Press). Several of his methods and tools have been patented and commercialized for clinical use in the largest hospitals in Vietnam through the company GeneStory, which he co-founded. His work helps implement precision medicine in healthcare in Vietnam and around the world.