Organized by:
Jingyi Jessica Li, University of California, Los Angeles
Chaolin Zhang, Columbia University
Qiangfeng Cliff Zhang, Tsinghua University
COURSE DESCRIPTION
Technologies such as next-generation sequencing (NGS) that generate massive genomic datasets have transformed every aspect of molecular biology research. The Computational Genomics course teaches state-of-the-art genomic technologies, principles of key computational algorithms and statistical models to analyze datasets generated from these technologies, and applications in various research domains. The course covers broad topics including:
Deep sequencing analysis
Single cell and spatial transcriptomics
Gene regulatory networks
Protein structure prediction
Statistical genomics/genetics
AI/machine learning
Lectures are complemented with hands-on sessions during which students will conduct “mini projects” of genomic data analysis. Emphasis will be placed on understanding the interplay between experimental design, data acquisition, and data analysis so that students can apply these powerful tools in their own research. The course aims at training talented and highly motivated students and postdoctoral fellows from Asia and around the world who plan to become computational biologists to perform cutting-edge genomic research.
2025 FACULTY ROSTER
Kin Fai Au, University of Michigan Medical School
Stefan Canzar, University of Regensburg
Ge Gao, Peking University
Jingyi Jessica Li, University of California, Los Angeles
Tingting Li, Peking University
Kirk Lohmueller, University of California, Los Angeles
Xiang-Jun Lu, Columbia University
Lianrong Pu, Shandong University
Jian Yang, Westlake University
Li Yang, Fudan University
Chaolin Zhang, Columbia University
Michael Zhang, University of Texas at Dallas
Qiangfeng Cliff Zhang, Tsinghua University
Xuegong Zhang, Tsinghua University
Yaoqi Zhou, Shenzhen Bay Labratory
2025 PRICING (INCLUDING TUITION, BOARD AND LODGING): 1400 USD
No payment is due until the selection decisions are made, but any applicant requiring financial support (i.e. stipends) should make that request in written form during the online application. The admissions process is need-blind, your financial situation will not be considered before admission decisions are made.