Representations and Algorithms for Computational Molecular Biology (BIOE 214, BMDS 214, CS 274)

1–4 credits · Graduate

Topics: This is a graduate level introduction to bioinformatics and computational biology.  This is a programming class in Python with substantial programming required.  Topics include algorithms for both pairwise and multiple sequence alignment of biological sequences and structures, phylogenetic tree construction, hidden Markov models, basic structural computations on proteins, protein structure prediction, protein language models, molecular dynamics and energy minimization, statistical analysis of 3D biological data, integration of data sources, knowledge representation and controlled terminologies for molecular biology, intro to transcription analysis, chemoinformatics, pharmacogenetics, network biology. Firm prerequisite: CS 106B.