BTRY 4381
Last Updated
- Schedule of Classes - February 12, 2019 8:29PM EST
- Course Catalog - January 26, 2019 2:00PM EST
Classes
BTRY 4381
Course Description
Course information provided by the 2018-2019 Catalog.
A biomedical data science course using Python and available bioinformatics tools and techniques for the analysis of molecular biological data, including biosequences, microarrays, and networks. This course emphasizes practical skills rather than theory. Topics include advanced Python programing, R and Bioconductor, sequence alignment, MySQL database (DBI), web programing and services (CGI), genomics and proteomics data mining and analysis, machine learning, and methods for inferring and analyzing regulatory, protein-protein interaction, and metabolite networks.
Prerequisites/Corequisites Prerequisite: at least one introductory course in computer programming (any language) and one in statistical methods, or permission of the instructor.
Outcomes
- Demonstrate familiarity with the basics of applied statistical methodology.
- Demonstrate familiarity with statistical software and a programming language.
- Demonstrate ability to perform complex data mining of biological datasets using a programming language.
- Demonstrate ability to effectively communicate the results of a statistical analysis to biologists.
- Demonstrate familiarity with statistical and computational tools for high throughput genomic data.
- Demonstrate ability to build stand-alone softwares, web tools, and databases for analyzing biological data.
When Offered Fall.
Regular Academic Session. Choose one lecture and one laboratory. Combined with: BTRY 6381
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Credits and Grading Basis
3 Credits Graded(Letter grades only)
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Class Number & Section Details
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Meeting Pattern
- T Comstock Hall-Academic II B108
Instructors
Yu, H
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Additional Information
Instruction Mode: In Person
Prerequisite: at least one introductory course in computer programming (any language) and one in statistical methods, or permission of the instructor.
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Class Number & Section Details
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Meeting Pattern
- R Fernow Hall G24
Instructors
Yu, H
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Additional Information
Instruction Mode: In Person
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