Exploring cis-regulatory models of the genome to predict epigenetic state and variation
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
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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/1721.1/106117 |
| _version_ | 1826193246727962624 |
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| author | Kang, Daniel D |
| author2 | David Gifford. |
| author_facet | David Gifford. Kang, Daniel D |
| author_sort | Kang, Daniel D |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. |
| first_indexed | 2024-09-23T09:35:57Z |
| format | Thesis |
| id | mit-1721.1/106117 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:35:57Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1061172019-04-10T15:59:28Z Exploring cis-regulatory models of the genome to predict epigenetic state and variation Kang, Daniel D David Gifford. 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: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages [18]-[20]). We introduce a new model called CCM+ that rectifies the inability of previous sequence-based methods to generalize across cell-types. We permit generalization by introducing arbitrary base-pair resolution covariates. We show that the addition of base-pair resolution chromatin accessibility covariate greatly aids in the prediction of cis-regulatory marks. Additionally, we show that by using cell-type specific covariates, CCM+ can generalize across cell-types. Finally, we show CCM+ can be used for downstream analysis that matches state-of-the-art methods when chromatin accessibility is used as a covariate. by Daniel Kang. M. Eng. 2016-12-22T16:29:41Z 2016-12-22T16:29:41Z 2015 2015 Thesis http://hdl.handle.net/1721.1/106117 965798517 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 27 unnumbered pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Kang, Daniel D Exploring cis-regulatory models of the genome to predict epigenetic state and variation |
| title | Exploring cis-regulatory models of the genome to predict epigenetic state and variation |
| title_full | Exploring cis-regulatory models of the genome to predict epigenetic state and variation |
| title_fullStr | Exploring cis-regulatory models of the genome to predict epigenetic state and variation |
| title_full_unstemmed | Exploring cis-regulatory models of the genome to predict epigenetic state and variation |
| title_short | Exploring cis-regulatory models of the genome to predict epigenetic state and variation |
| title_sort | exploring cis regulatory models of the genome to predict epigenetic state and variation |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/106117 |
| work_keys_str_mv | AT kangdanield exploringcisregulatorymodelsofthegenometopredictepigeneticstateandvariation |