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Evolutionary and Ecological Bioinformatics

BIOL 327
Fall 2015
Section: 01  
Crosslisting: COMP 327, BIOL 527, COMP 527, CIS 327
Certificates: Environmental Studies, Informatics and Modeling

Bioinformatic analysis of gene sequences and gene expression patterns has added enormously to our understanding of ecology and evolution. For example, through bioinformatic analysis of gene sequences, we can now reconstruct the evolutionary history of physiology, even though no traces of physiology exist in the fossil record. We can determine the adaptive history of one gene and all the gene's descendants. We can now construct the evolutionary tree of all of life. Bioinformatics is particularly promising for analysis of the ecology and biodiversity of microbial communities, since well over 99 percent of microorganisms cannot be cultured; our only knowledge of these organisms is through analysis of their gene sequences and gene expression patterns. For example, even when we cannot culture most of a microbial community, we can determine which metabolic pathways are of greatest significance through analysis of community-level gene expression. All these research programs are made accessible not only by breakthroughs in molecular technology, but also by innovation in the design of computer algorithms. This course, team-taught by an evolutionary biologist and a computer scientist, will present how bioinformatics is revolutionizing evolutionary and ecological investigation and will present the design and construction of bioinformatic computer algorithms underlying the revolution in biology. Students will learn algorithms for reconstructing phylogeny, for sequence alignment, and for analysis of genomes, and students will have an opportunity to create their own algorithms.
Credit: 1 Gen Ed Area Dept: NSM BIOL
Course Format: LectureGrading Mode: Graded
Level: UGRD Prerequisites: [BIOL182 or MB&B182] OR [BIOL196 or MB&B196] OR COMP112 OR COMP211
Fulfills a Major Requirement for: (BIOL)(CIS)(COMP)(ENVS-MN)(ENVS)(NS&B)
Past Enrollment Probability: 75% - 89%

Last Updated on SEP-29-2023
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