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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.

Fall 2022 Computer Science E4762 section 001
Machine Learning for Functional Genomics
ML for Functional Genomic

Call Number 11026
Day & Time
MW 4:10pm-5:25pm
451 Computer Science Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor David A Knowles
Method of Instruction In-Person
Course Description This course will introduce modern probabilistic machine learning methods using applications in data analysis tasks from functional genomics, where massively-parallel sequencing is used  to measure the state of cells: e.g. what genes are being expressed, what regions of DNA (“chromatin”) are active (“open”) or bound by specific proteins. 
Web Site Vergil
Department Computer Science
Enrollment 73 students (100 max) as of 8:06AM Wednesday, December 7, 2022
Subject Computer Science
Number E4762
Section 001
Division School of Engineering and Applied Science: Graduate
Campus Morningside
Section key 20223COMS4762W001

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SIS update 12/07/22 08:06    web update 12/07/22 08:31