NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information. | |
Spring 2021 Computer Science E4762 section 001 Machine Learning for Functional Genomics ML for Functional Genomic | |
Call Number | 12573 |
Day & Time Location |
MW 4:10pm-5:25pm ONLINE ONLY |
Points | 3 |
Grading Mode | Standard |
Approvals Required | None |
Instructor | David A Knowles |
Type | LECTURE |
Method of Instruction | On-Line Only |
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 | 59 students (100 max) as of 4:03PM Wednesday, April 21, 2021 |
Subject | Computer Science |
Number | E4762 |
Section | 001 |
Division | School of Engineering and Applied Science: Graduate |
Campus | Morningside |
Section key | 20211COMS4762W001 |
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