<?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>2026-09-20T12:09:09Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/108971" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/108971</identifier><datestamp>2026-06-16T18:16:16Z</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">Timothy K. Lu.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Cui, Cheryl H. (Cheryl Hao)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Harvard--MIT Program in Health Sciences and Technology.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Harvard University--MIT Division of Health Sciences and Technology</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2017-05-11T19:58:30Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2017-05-11T19:58:30Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/108971</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">986497010</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: Ph. D. in Medical Engineering and Medical Physics, Harvard-MIT Program in Health Sciences and Technology, 2017.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 124-135).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The complex, dynamic, and responsive behavior of cells arises from integrated signaling pathways and regulatory networks. With advancement in our ability to engineer mammalian cells, we harness a novel set of molecular tools to develop synthetic biology-enabled applications that help facilitate our understanding of complex biological networks and cellular behaviors. The recent discovery of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated (Cas) system from prokaryotic adaptive immune system demonstrated unprecedented genome editing efficiency and programmability in sequence specific genome editing of mammalian cells. In this thesis, I utilized the CRISPR-Cas system to construct a combinatorial genetic perturbation platform that enables massively parallel high throughput screening of multiple gene elements. This technology platform allows systematically interrogation of higher-order interactions of genetic regulators. The later part of the work described the establishment of a genomically encoded cellular recorder with the ability to longitudinally track and record molecular events in live animals. This cellular recorder encodes cellular memory through the quantitative accumulation of targeted genomic mutations, that allows mapping of a dynamical set of gene regulatory events without the need for continuous cell imaging or destructive sampling. Together, we envision these sets of technology and tools will offer new insights into cellular process in disease and in health.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Cheryl H. Cui.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D. in Medical Engineering and Medical Physics</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">181 pages</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">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written 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">Harvard--MIT Program in Health Sciences and Technology.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Decipher in situ signaling and complex genetics with cellular recording and combinatorial perturbations</dim:field>
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   	&lt;Title>Decipher in situ signaling and complex genetics with cellular recording and combinatorial perturbations&lt;/Title>
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   	&lt;PublicationDate>2017&lt;/PublicationDate>
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        	&lt;DisplayName>Cui, Cheryl H. (Cheryl Hao)&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;Keyword>Harvard--MIT Program in Health Sciences and Technology.&lt;/Keyword>
   	&lt;Abstract>The complex, dynamic, and responsive behavior of cells arises from integrated signaling pathways and regulatory networks. With advancement in our ability to engineer mammalian cells, we harness a novel set of molecular tools to develop synthetic biology-enabled applications that help facilitate our understanding of complex biological networks and cellular behaviors. The recent discovery of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated (Cas) system from prokaryotic adaptive immune system demonstrated unprecedented genome editing efficiency and programmability in sequence specific genome editing of mammalian cells. In this thesis, I utilized the CRISPR-Cas system to construct a combinatorial genetic perturbation platform that enables massively parallel high throughput screening of multiple gene elements. This technology platform allows systematically interrogation of higher-order interactions of genetic regulators. The later part of the work described the establishment of a genomically encoded cellular recorder with the ability to longitudinally track and record molecular events in live animals. This cellular recorder encodes cellular memory through the quantitative accumulation of targeted genomic mutations, that allows mapping of a dynamical set of gene regulatory events without the need for continuous cell imaging or destructive sampling. Together, we envision these sets of technology and tools will offer new insights into cellular process in disease and in health.&lt;/Abstract>
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