Deep learning in-vivo transcription factor binding
Abstract/Contents
- Abstract
- Transcription factors (TFs) affect gene expression by interpreting regulatory DNA within a genome. Models of DNA sequence and shape can explain in-vitro TF-DNA interactions outside a cellular context. But in-vivo TF-DNA interactions in cells are influenced by additional factors, such as interactions between TFs, and interactions between TFs and nucleosomes. Here, we present the application of deep learning, a class of modern machine learning techniques, to the task of modeling in-vivo transcription factor binding at a genome-wide scale. Deep learning has powered significant breakthroughs in complex pattern recognition tasks across several data-rich domain and successful applications have primarily focused on image, speech, and text data modalities. In this thesis, we present three new contribution to the field of deep learning applications to genomics: (1) Adapation of deep learning methods to regulatory DNA sequence data using simulations, (2) development of deep learning models of in-vivo TF binding at a genome-wide scale, and (3) interrogations of these models to reveal determinants of in-vivo TF binding sites. Our results demonstrate that deep learning can be used to build accurate, interpretable models of in-vivo TF binding. That there are guiding principles to systematic development and interpretation of such models. Finally, we discuss limitations of our methods and point to directions for future work.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Israeli, Yonatan |
|---|---|
| Degree supervisor | Kundaje, Anshul, 1980- |
| Thesis advisor | Kundaje, Anshul, 1980- |
| Thesis advisor | Altman, Russ |
| Thesis advisor | Fordyce, Polly |
| Thesis advisor | Greenleaf, William James |
| Degree committee member | Altman, Russ |
| Degree committee member | Fordyce, Polly |
| Degree committee member | Greenleaf, William James |
| Associated with | Stanford University, Biophysics Laboratory. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Yonatan (Johnny) Israeli. |
|---|---|
| Note | Submitted to the Biophysics Laboratory. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Yonatan Israeli
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
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