CS 6522: Biological Sequence Analysis

Cross-Listing: Not cross-listed.

Alignment of biological sequences (DNA, AA, RNA) features prominently in modern biological and computational biology research. In this course we will study in detail the statistical and algorithmic challenges that one faces in designing tools for alignment. For example, how do we find an optimal local alignment between a query sequence and a genomic database and how do we know whether or not such an alignment is statistically significant? Following Durbin et al.'s textbook we will start with presenting sequence and multiple sequence alignment algorithms in the context of probabilistic models (extensions of HMM, covariance models). We will also go over Karlin and Altschul and others' work on the statistical analysis of alignments. Building on these "classical" results we will address more current topics such as seed design for the seeded alignment paradigm and alignment questions that came up in recent whole genome comparisons such as the rat-human-mouse one.

Offered: Fall only

Prerequisites: Some familiarity with algorithms, statistics, and probability is suggested.

Grade options: Letter only

Credit hours: 4

Recent offerings:

• http://www.cs.cornell.edu/courses/cs628/2007fa
  • Uri Keich
• http://www.cs.cornell.edu/courses/cs628/2006fa
• http://www.cs.cornell.edu/courses/cs628/2006sp
  • Uri Keich