Computational Genomics Summer 2026
Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center
Adjunct Faculty, Department of Systems and Computational Biomedicine, Weil Cornell Medical College
Course Overview
Welcome to Computational Genomics, a computer workshop for graduate students. A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and next-generation DNA -sequencing technologies, biomedical sciences are undergoing a rapid and irreversible transformation into a highly data-intensive field.
Genome information is revolutionizing virtually all aspects of life sciences including basic research, medicine, and agriculture. Meanwhile, use of genomic data requires life scientists to be familiar with concepts and skills in biology, computer science, as well as data analysis.
This workshop is designed to introduce computational analysis of genomic data through hands-on computational exercises, using published studies.
The pre-requisites of the course are college-level courses in molecular biology, cell biology, and genetics. Introductory courses in computer programming and statistics are preferred but not strictly required.
Learning goals
By the end of this course successful students will be able to:
- (Pop Gen) Achieve an algorithmic understanding of major evolutionary processes (drift, mutation, recombination, and natural selection)
- (Computation) Implement the evolutionary algorithms in a programming language of choice (R, Python, or others)
- (Phylogenomics) Compare and analyze genomes in a phylogenetic framework
- (Microbial evolution) Understand the distinctions between microbial and eukaryotic evolution
Web Links
- Install R base: https://cloud.r-project.org
- Install R Studio (Desktop version): http://www.rstudio.com/download
- R/Tidyverse reference book: R for Data Science (Wickharm et al)
- A textbook on microbial genomics & evolution by the instructor: Digital Genomes (Qiu 2026)
Assignments, Quizzes, and a Final Presentatio8n
Student performance will be evaluated by attendance, three (3) quizzes and a final presentation
- Attendance & participation: 12 * 5 pts = 60 pts
- Daily assignments: 8 x 10 pts = 80 pts
- Open-Book Quizzes: 3 x 30 pts = 60 pts
- Final presentation: 30 pts
Total: 230 pts
Course Schedule
Week 1
Session 1 (7/13)
- Introduction. Lecture slides: File:QiuLab-CUNY-Hunter.pdf
- Gitee accounts & usage Course link on gitee; Demo: homework submission using Gitee
- Survey 1: Genomics & Data Science PDF file: File:KIZ-survey-1.pdf
- Survey 2: Tree-thinking Skills PDF file: File:Pretest-1.pdf
- Lecture: Tree-thinking Skills. Lecture slides: File:Phylogeny-lecture-slides-2024.pdf
Session 2 (7/14)
- Git usages (by Mr Liu)
- Download the course repository:
git clone https://gitee.com/huntercollege/comp-genomics-kiz.git
- Download the course repository:
- Linux Tutorial I. File:Intro-unix-KIZ.pdf
- Tree manipulations: reroot & tree distances
- Gene tree vs Species tree; orthologous and paralogous genes; tree pruning & collapsing
Session 3 (7/16)
- Quiz #1
- Linux Tutorial II: BpWrapper Toolkit (https://github.com/bioperl/p5-bpwrapper) Updated sldies: File:Intro-unix-KIZ.pdf
Week 2
Session 4 (7/20)
Session 5 (7/21)
Session 6 (7/23)
- Quiz #2
Week 3
Session 7 (7/27)
Session 8 (7/28)
Session 9 (7/30)
- Quiz #3
Week 4
Session 10 (8/3)
Session 11 (8/4)
Session 12 (8/6)
- Quiz #4
Week 5
Session 13 (8/10)
Session 14 (8/11)
- Presentations
Session 15 (8/13)
- Presentations
- Course evaluation