2026-09-21T03:49:20Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1037492022-01-13T07:54:01Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Manolis Kellis.
Grzadkowski, Michal R
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2016-07-18T20:06:07Z
2016-07-18T20:06:07Z
2016
2016
http://hdl.handle.net/1721.1/103749
953583303
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.
95 pages
eng
Massachusetts Institute of Technology
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
Electrical Engineering and Computer Science.
Inferring the properties of transcription factor regulation
Thesis
application/pdf
Publication
unknown
unknown
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