상세정보
Export to Refworks부가기능
Building Gene Regulatory Networks Using Self-Organizing Maps
상세 프로파일
| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Building Gene Regulatory Networks Using Self-Organizing Maps. |
| 개인저자 | Jansen, Camden . |
| 단체저자명 | University of California, Irvine. Biological Sciences - Ph.D.. |
| 발행사항 | [S.l.]: University of California, Irvine., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 138 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-02B. Dissertation Abstract International |
| ISBN | 9781085704595 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Irvine, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-02, Section: B.
Advisor: Mortazavi, Ali. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | Gene expression is a tightly controlled process in all cells and at all stages of life. Expressing the wrong gene at the wrong time in the wrong cell can be deadly to an organism and is one of the hallmarks of disease. The primary point of control of gene expression is transcriptional regulation, which is the process gating the transcription of a gene into mRNA. This process is largely controlled by protein-DNA interactions where specific proteins recognize a specific DNA sequence potentially in combination with other proteins in order to bind to that location and either recruit or repel the general transcriptional machinery. These protein-DNA interactions can be abstracted into connections on a gene regulatory network (GRN) for visualization. GRNs have been drawn for many cellular functions from the bottom-up, in which each interaction is exhaustively studied one-at-a-time, representing months or years of work. In this thesis, I present two works that build these networks from the top-down with self-organizing maps using (1) single cell gene expression and single cell chromatin accessibility drawn from a mouse pre-B cell differentiation system and (2) a large dataset of bulk functional genomics assays of mesendodermal development in Xenopus tropicalis. The resulting networks not only recapitulate known interactions, but they also introduce a large number of new potential regulatory connections for each system. Finally, I present a process for performing this analysis on a growing dataset with iterative releases without requiring a full re-classification. In all, the results of this work provide a novel way to study the regulation of gene expression using integrative analysis of large functional genomics datasets. |
| 일반주제명 | Cellular biology. Developmental biology. Bioinformatics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
