Applied Genomics: Introduction to Bioinformatics and Network Modeling
BIOL-GA 1130
Fundamental methods of analyzing large data sets from genomics experiments, including hands-on computational training. Analysis focuses on data from genome-wide studies of gene expression using microarrays and from genome-wide studies of molecular interactions. Methods covered include clustering, multiple-hypothesis testing, and network inference.
Undergrad students must request a registration code from Emilio Del Valle (ejd8766@nyu.edu)
Format: Lecture, Recitation
Prerequisites: Masters Students - BIOL-GA 2030 OR permission of the instructor. Must have programming experience (R or Python preferred.), Undergraduate Students - (BIOL-UA 21 and BIOL-UA 22) and (BIOL-UA 42 and BIOL-UA 45 or BIOL-UA 103)
Corequisites: None
Location: New York
Equivalent(s): None
Course Description
Term(s) offered:
Requirements satisfied:
- Major: Biology Standard Track
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- Upper-Level Elective
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- Quantitative Skills
- Advanced Biology
- Major: Ecology Track
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- Upper-Level Elective
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- Advanced Biology
- Major: GPH/Biology
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- Additional Elective
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- Minor: Genomics & Bioinformatics
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- Elective
-
-
- Upper-Level Elective
-
- Quantitative Skills
- Advanced Biology
-
- Upper-Level Elective
-
- Upper-Level Elective
-
- Advanced Biology
-
- Upper-Level Elective
-
- Additional Elective
- Additional Elective
-
- Elective
- Elective