| Computational Genomics - 21888 - BCHM 42200 - 001 |
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Associated Term: Fall 2022
Levels: Graduate, Professional, Undergraduate West Lafayette Campus Lecture Schedule Type Learning Outcomes: • Evaluate features of a genome (e.g. conservation, GC content, gene coding potential) • Understand how data from next-generation sequencing experiments (e.g. RNA-seq, ChIP-seq, Exome-seq) are generated and processed • Analyze next-generation sequencing data (e.g. RNA-seq, ChIP-seq) from various experiments • Integrate various genomics data to answer specific biological question related to genomics and gene regulation Required Materials: Textbooks below are not required but are great additional resources and are also on reserve at the Hicks Undergraduate Library and/or the Lilly Life Sciences library. Textbooks • Introduction to Genomics 3rd Edition, Arthur Lesk, 2017 • Bioinformatics and Functional Genomics 3rd Edition, Jonathan Pevsner, 2015 • Bioinformatics Algorithms: An Active Learning Approach, Phillip Compeau and Pavel Pevzner, 2014 Online resources • http://www.ee.surrey.ac.uk/Teaching/Unix/ • http://www.cyclismo.org/tutorial/R/ Brightspace • The syllabus for the course, lecture notes, and grading keys for quizzes and exams will be available via the Purdue University Brightspace at https://purdue.brightspace.com/ Technical Requirements: Some knowledge or experience with programing and basic molecular biology is welcomed but not required. Necessary concepts from biology, statistics, and computational algorithms will be provided during the course. View Catalog Entry
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