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COMP.3500/5800.202
Topics in CS: Bioinformatics
Spring 2017
Office Hrs: Mon 3:00-5:00 pm
Instructor: Byung Kim, [email protected]
Course webpage: TBD
Textbook: St. Clair & Visick, “Exploring Bioinformatics,” Jones and Bartlett, 2nd ed., 2015
Recommended Books:
Jonathan Pevsner, “Bioinformatics and Functional Genomics,” 2nd ed., Wiley-Blackwell, 2009
Paul Higgs and Tersa Attwood, "Bioinformatics and Molecular Evolution," Blackwell Pub., 2005.
Neil Jones and Pavel Pevzner, "An Intro. to Bioinformatics Algorithms," MIT Press, 2004
Arthur Lesk, “Introduction to Bioinformatics,” 3rd ed., Oxford Univ. Press, 2008
Outline:
Complete genomic sequences of human, other mammals, and numerous other organisms are
known for some time. From early on, comparisons or analyses of genomic sequences require
aids of computer programming.
After brief introductions to molecular biology for CS students and computer algorithms for
biology students, the course will examine computer algorithms used in bioinformatics problems.
Major topics to be covered are as follows:
1. Sequence Alignment: Aligning multiple sequences is based on a dynamic algorithm, and
allows one to compare the sequences.
2. Clustering: Data points from multiple attributes need to be grouped in terms of their
similarities. Neural networks and SVM (Support Vector Machine)
3. Sequencing algorithms: All DNA sequences start by assembling millions short reads. Next
generating sequencing algorithms will be studied.
4. Phylogeny: Modeling of gene evolutions can lead to phylogenetic trees.
5. Inference and prediction models: Hidden Markov Model (HMM) and Data Mining models
6. Protein structures
Evaluation:
Mid-term and Final tests – 30 % each
HW & Programming assignments – 40 %
Sequence alignment with dynamic programming
Clustering of amino acids
Gene prediction
Notes:
 Co-listed for undergraduate and graduate courses