Inferring the properties of transcription factor regulation
Author(s)
Grzadkowski, Michal R
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Manolis Kellis.
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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.
Description
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).
Date issued
2016Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.