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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. | |
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 | 66 students (100 max) as of 11:34AM Wednesday, January 27, 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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