Computational Biology Resources at Colorado State University
Course Offerings
Course across multiple different departments at CSU can provide foundational skills in the analysis of large biological data sets.
Biology
- BZ 360: Bioinformatics and Genomics
MIP
- MIP 280A4: Microbial Sequence Analysis
Computer Science
- CS 150: Interactive Programming with Java
- CS 152: Introductory Python Programming
Statistics
- STAT 301: Introduction to Statistical Methods
- STAT 307: Introduction to Biostatistics
- STAT 315: Statistics for Engineers and Scientists
- Growing number of online modules and programs in applied statistics
Research Landscape
Research labs throughout the university are employing computational and quantitative tools to address biological questions. Here are some examples of the many labs distributed across campus.
Biology
- Chris Funk: Population and Conservation Genomics
- Tai Montgomery: Small RNAs and Functional Genomics
- Rachel Mueller: Transposable Elements and Evolutionary Genomics
- Anireddy Reddy: Gene Regulation and Functional Genomics
- Kristen Ruegg: Avian population genetics and genomics
- Dan Sloan: Molecular Evolution and Genomics
- Colleen Webb: Disease Modeling
- …and many more with genomic, transcriptomic, and/or proteomic components to their research
Biochemistry and Molecular Biology
- Erin Nishimura: Single-Cell Transcriptomics
Chemical and Biological Engineering
- Brian Munsky: Modeling Complex Biological Systems
- Jean Peccoud: Synthetic Biology
- Christie Peebles: Metabolic Engineering and Systems Biology
- Ashok Prasad: Systems Biology
- Chris Snow: Computational Analysis and Design of Molecular Structures
College of Agriculture
- Marek Borowiec: Phylogenetics, Bioinformatics, and Deep Learning
- Todd Gaines: Herbicide Resistance and Functional Genomics
- Jan Leach: Plant-Microbe Interactions
- Jessica Metcalf: Microbiomes
- John McKay: Local Adaptation and Evolutionary Genomics
- Jane Stewart: Plant Pathology and Genomics
College of Veterinary Medicine and Biomedical Sciences
- Zaid Abdo: Microbiomes
- Greg Ebel: Viral Genomics
- Mark Stenglein: Viral Genomics and Pathogen Detection
- …and many more with genomic, transcriptomic, and/or proteomic components to their research
Computer Science
- Asa Ben-Hur: Bioinformatic Algorithms and Machine Learning
Statistics
- Wen Zhou: Statistical Genomics and Bioinformatics
Supported by the National Science Foundation (MCB-1733227 and IOS-1829176).