CSCE/BICH 628 Computational Biology
Fall 22

What is Computational Biology

Computational Biology is the application of computational techniques to solve problems in biology, which involves DNA and proteins. Traditionally, people from various disciplines, such as computer science, mathematics and statistics, formulate and address these problems within their own disciplines. More recently, multi-disciplinary collaborations become the norm, which include participations of biologists and biochemists.

Goal

The main purpose of the course is to expose students to various areas in computational biology. Everyone who is interested in computational biology is encouraged to take the course. The course is suitable for life science students with limited computational background. Emphasis will be placed on problem formulations, where many problems in genomics and proteomics are seen as graph-theoretic or optimization problems. No programming experience is needed. The course will focus on understanding the main ideas behind these approaches.

Topics

• Computational formulations and algorithms for biological sequence comparisons.
• Combinatorial and statistical approaches to motif finding and applications.
• Scalable algorithms for comparative genomics and whole genome comparisons.
• Approaches for gene clustering and protein classification.
• Study of genome rearrangements and inferring evolutionary relationships.
• Algorithms for finding common substructures in biological networks.
• Techniques for high-throughout sequence analysis.

Grading

• Homework assignments (60%): short written assignments handed out every one or two weeks.
• Two midterms (20% each).

Prerequisites

• Graduate classification or approval of instructor.