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Our lab is committed to:
Bridging computational science and biomedical research to drive biological discoveries in cancer genomics and epigenomics.
Developing AI-driven methodologies to deepen our understanding of biological phenomena and improve medical diagnostics and treatment strategies.
Training the next generation scientists through the cutting-edge research and interdisciplinary collaboration.
Our primary research areas include:
Cancer Genomics & Tumor Microenvironments
Cancer Genomics & Tumor Microenvironments
Identification of cancer biomarkers for subtype classification and personalized therapy
Analysis of tumor evolution, heterogeneity, and resistance mechanisms
Characterizing tumor microenvironments and tumor immune system
Prediction of immunotherapy response and treatment outcomes
Machine Learning for Biomedical Research
Machine Learning for Biomedical Research
Development of machine learning and deep learning models to analyze biomedical datasets
AI-based modeling to uncover hidden patterns in biomedical systems
Enhancing medical diagnostics and drug response predictions through computational intelligence.
Genomics, Transcriptomics, Epigenomics and Multi-omics
Genomics, Transcriptomics, Epigenomics and Multi-omics
Comprehensive analysis of genomic, transcriptomic, and epigenomic data to uncover regulatory mechanisms in disease.
Investigation of 3D chromatin architecture and epigenetic regulation using advanced techniques such as Hi-C and scHi-C.
Biomarker discovery through large-scale data integration
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