<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-20T00:41:52Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/43222" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/43222</identifier><datestamp>2022-01-13T07:54:15Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Richard A. Young.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Cole, Megan F</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Biology.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Biology</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2008-11-07T19:17:41Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2008-11-07T19:17:41Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2008</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2008</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/43222</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">259223829</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2008.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The process by which a single fertilized egg develops into a human being with over 200 cell types, each with a distinct gene expression pattern controlling its cellular state, is poorly understood. An understanding of the transcriptional regulatory networks that establish and maintain gene expression programs in mammalian cells is fundamental to understand development and should provide the foundation for improved diagnosis and treatment of disease. Although it is not yet feasible to map the entirety of these networks in vertebrate cells, recent work in embryonic stem (ES) cells has demonstrated that core features of the network can be discovered by focusing on key transcriptional regulators and their target genes. Here, I describe important insights that have emerged from such studies and highlight how similar approaches can be used to discover the core networks of other vertebrate cell types. Knowledge of the regulatory networks controlling gene expression programs and cell states can guide efforts to reprogram cell states and holds great promise for both disease therapeutics and regenerative medicine.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Megan F. Cole.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">256 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">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.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Biology.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Dissecting the transcriptional regulatory network of embryonic stem cells</dim:field>
   <dim:field mdschema="dc" element="type" lang="en_US">Thesis</dim:field>
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   	&lt;Title>Dissecting the transcriptional regulatory network of embryonic stem cells&lt;/Title>
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   	&lt;PublicationDate>2008&lt;/PublicationDate>
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        	&lt;DisplayName>Cole, Megan F&lt;/DisplayName>
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    &lt;Keyword>Biology.&lt;/Keyword>
   	&lt;Abstract>The process by which a single fertilized egg develops into a human being with over 200 cell types, each with a distinct gene expression pattern controlling its cellular state, is poorly understood. An understanding of the transcriptional regulatory networks that establish and maintain gene expression programs in mammalian cells is fundamental to understand development and should provide the foundation for improved diagnosis and treatment of disease. Although it is not yet feasible to map the entirety of these networks in vertebrate cells, recent work in embryonic stem (ES) cells has demonstrated that core features of the network can be discovered by focusing on key transcriptional regulators and their target genes. Here, I describe important insights that have emerged from such studies and highlight how similar approaches can be used to discover the core networks of other vertebrate cell types. Knowledge of the regulatory networks controlling gene expression programs and cell states can guide efforts to reprogram cell states and holds great promise for both disease therapeutics and regenerative medicine.&lt;/Abstract>
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