Inferring the properties of transcription factor regulation
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/103749 |
| _version_ | 1826208063336480768 |
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| author | Grzadkowski, Michal R |
| author2 | Manolis Kellis. |
| author_facet | Manolis Kellis. Grzadkowski, Michal R |
| author_sort | Grzadkowski, Michal R |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. |
| first_indexed | 2024-09-23T13:59:55Z |
| format | Thesis |
| id | mit-1721.1/103749 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T13:59:55Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1037492019-04-11T07:00:29Z Inferring the properties of transcription factor regulation Grzadkowski, Michal R Manolis Kellis. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 93-95). The regulatory targets of transcription factors are costly to directly detect using existing technologies. Many computational models have thus been developed to infer the genes targeted by TFs using gene expression profiles, position weight matrices modeling TF protein binding, histone modifications, and other secondary datasets. We develop a framework for scoring the potential targets of various TFs using models that take the profile of motif hits on the proximity of transcription start sites as input, and describe methods to validate this framework using expression datasets. These models are then extended to include cis-regulatory regions inferred from epigenetic data. by Michal R. Grzadkowski. S.M. 2016-07-18T20:06:07Z 2016-07-18T20:06:07Z 2016 2016 Thesis http://hdl.handle.net/1721.1/103749 953583303 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 95 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Grzadkowski, Michal R Inferring the properties of transcription factor regulation |
| title | Inferring the properties of transcription factor regulation |
| title_full | Inferring the properties of transcription factor regulation |
| title_fullStr | Inferring the properties of transcription factor regulation |
| title_full_unstemmed | Inferring the properties of transcription factor regulation |
| title_short | Inferring the properties of transcription factor regulation |
| title_sort | inferring the properties of transcription factor regulation |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/103749 |
| work_keys_str_mv | AT grzadkowskimichalr inferringthepropertiesoftranscriptionfactorregulation |