Lab Introduction

Bioinformatics Laboratory (BioInfo Lab) at Hanoi University of Science and Technology focuses on developing computational methods, artificial intelligence, and data-driven approaches to address challenging problems in modern biology and biomedicine. As biological data continues to grow rapidly, our laboratory aims to transform large-scale biological data into meaningful knowledge and practical biomedical applications.

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News

Foundation Models that Can ‘Act or Defer’

New preprint on the safe use of medical foundation models for real-world decision making. [Project website]

Overton Prize

Our research has been recognized with the 2026 Overton Prize.

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Our Research Areas

Drug Discovery

Drug Discovery research aims to accelerate the identification of new drugs and therapeutic strategies using [...]

Genome Analysis

Genome Analysis focuses on decoding, processing, and interpreting large-scale genomic data to understand genetic variation [...]

Forensic DNA Profiling

Forensic DNA Profiling applies bioinformatics and genomic technologies to human identification and forensic investigations. DNA [...]

Persionalized Medicine

Personalized Medicine focuses on tailoring healthcare and treatment strategies based on individual genetic profiles and [...]

Featured Publications

DSCC: disease subtyping using spectral clustering and community detection from consensus networks

Molecular subtyping is fundamental in cancer research and clinical management of cancer, guiding treatment planning, monitoring …

Cell type annotation using large language models (LLMs) and CytoAnalyst

Motivation Cell annotation is fundamental for single-cell data interpretation. Accurate annotation allows us to identify cell types, …

Featured Projects

Plant-based Diet Index and Risk of Pancreatic Cancer: Findings from a Prospective Cohort Study

Background: Data on the association between the plant-based diet and pancreatic cancer is sparse. We, therefore, examined associations …

Identifying representative sequences of protein families using submodular optimization

Identifying representative sequences for groups of functionally similar proteins and enzymes poses significant computational …

Members