Computational Genomics Approaches to Understanding Human Diseases and Cancer
Explore the interface of computational and experimental genomics to unravel cancer mechanisms. Develop innovative software and analyze vast omics datasets. Join a lab committed to mentorship, cutting-edge research, and scientific collaboration.
AI-generated overview
Project Description
Project Overview
This project aims to advance computational genomics approaches to better understand human diseases, particularly cancer, by integrating computational modeling with high-throughput experimental techniques. Research will focus on developing novel bioinformatics software and mining public multiomics datasets creatively and knowledgeably.
What You Will Do
Students and researchers will develop bioinformatics algorithms, analyze large-scale omics datasets, and contribute to high-throughput molecular and cellular biology experiments, including methods such as CRISPR screens. The lab emphasizes strong mentorship, career development, and collaboration with top-tier scientists for producing high-quality research outputs.
Expected Outcomes
Outcomes include novel computational tools, new biological insights into disease mechanisms, and contributions to the Human Cell Atlas and cancer genomics fields. Successful candidates will achieve strong publication records, secure external fellowships, and build impactful scientific networks.
Why This Matters
Understanding the complex genomics of diseases like cancer has profound implications for diagnostics, therapeutics, and personalized medicine. This work bridges computational and experimental genomics to accelerate discoveries that can transform healthcare.
Entry Requirements
How to Apply
Eligibility
Supervisor Profile
Dr. Qingnan Liang is a computational genomics researcher currently at the University of Oklahoma College of Medicine. He specializes in integrating computational modeling with high-throughput experiments to study human diseases, especially cancer. Previously, he was a postdoctoral associate at UT MD Anderson Cancer Center focusing on single-cell and spatial genomics and has contributed to the Human Cell Atlas project's multi-omics retina atlas. His work bridges bioinformatics and molecular biology to advance disease understanding.