R For Molecular Biosciences - 17303 - BCHM 49500 - 004 Link Id: A4  Linked Sections Required(A3) |
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Students will learn R to acquire, clean, explore and analyze biological data sets. Lectures and example data sets will show how data are linked to biological phenomena through human observation or instrumentation with inherent limitations. Students will learn how to organize data sets to optimize clarity and analytic possibilities while minimizing errors with examples drawn from the literature or biological databases. R programming will be taught starting with small-scale data such as drug sensitivity assays, qPCR, and metabolomics, moving to genome-scale analyses such as gene expression and pathway analysis later in the course. These skills will be taught in the light of enabling reproducible research through clear documentation of data sets and analyses. Relevant concepts from statistics will be reviewed, but it is assumed that students are familiar with basic statistical analyses.”
Associated Term: Spring 2020 Registration Dates: Oct 21, 2019 to Jan 20, 2020 Levels: Undergraduate, Graduate, Professional Attributes: Upper Division, Variable Title West Lafayette Campus Laboratory Schedule Type 0.000 Credits View Catalog Entry Course Materials
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| Comparative Genomics - 21301 - BCHM 49500 - 005 Link Id: A2 Linked Sections Required(A1) |
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Associated Term: Spring 2020
Registration Dates: Oct 21, 2019 to Jan 20, 2020 Levels: Undergraduate, Graduate, Professional Attributes: Upper Division, Variable Title West Lafayette Campus Laboratory Schedule Type 0.000 Credits View Catalog Entry Course Materials
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