STATS 547 - Probabilistic Modeling in Bioinformatics
Section: 001
Term: WN 2018
Subject: Statistics (STATS)
Department: LSA Statistics
Requirements & Distribution:
Advisory Prerequisites:
MATH, Flexible, due to diverse backgrounds of intended audience. Basic probability (level of MATH/STATS 425), or molecular biology (level of BIOLOGY 427), or biochemistry (level of CHEM/BIOLCHEM 451), or basic programming skills desirable or permission.
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
May not be repeated for credit.
Primary Instructor:

This course covers topics in Biological Sequence Analysis. Probabilistic models of proteins and nucleic acids. Analysis of DNA/RNA and protein sequence data. Algorithms for sequence alignment, statistical analysis of similarity scores, hidden Markov models, neural networks, training, gene finding, protein family profiles, multiple sequence alignment, sequence comparison, and structure prediction. Analysis of expression array data.

For more information on this course, please visit the Department of Mathematics webpage

STATS 547 - Probabilistic Modeling in Bioinformatics
Schedule Listing
001 (LEC)
TuTh 4:00PM - 5:30PM
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