This course is an interdisciplinary introduction to computational methods used to solve important problems in DNA and protein sequence analysis. The course focuses on algorithms but includes material to provide the necessary biological background for science and engineering students. Algorithms to be covered include dynamic programming for sequence alignment, such as Smith-Waterman, FASTA, and BLAST; hidden Markov models, such as the forward, Viterbi, and expectation maximization algorithms; a range of gene-finding algorithms; phylogenic tree construction; and clustering algorithms. Prerequisite(s): Familiarity with probability and statistics; working knowledge of Java, C++, C, Perl, MATLAB or Python; 605.205 Molecular Biology for Computer Scientists or a course in molecular biology; and a course in either cell biology or biochemistry.
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