<?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>2026-09-18T20:10:25Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/47880" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/47880</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">Amy E. Keating.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Gutwin, Karl N. (Karl Nickolai)</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">2009-10-01T15:57:47Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2009-10-01T15:57:47Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2009</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2009</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">433096679</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2009.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Page 224 blank.</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 alpha-helical coiled coil is a protein sequence and structural motif that consists of two or more helices in a parallel or antiparallel orientation supercoiling around a central axis. Coiled coils have been observed in a wide range of protein families, and many studies have focused on their sequence and structural diversity over the past half-century. In particular, the observation that coiled coils can be involved in determining protein-protein interactions and protein architectures has prompted the developments of methods to predict the structure of a coiled-coil complex from sequence information alone. In this thesis, I discuss the development of a structurally annotated database of coiled-coil sequence useful for training statistics-based methods of coiled-coil structure prediction. This database was used to retrain and stringently cross-validate the Multicoil method of predicting coiled-coil oligomerization state. In addition, I describe recent work using implicit and explicit structure models to predict dimeric coiled-coil orientation and alignment. Improvements to existing models, insight into coiled-coil structure determinants, and the future of coiled-coil prediction are also discussed.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Karl N. Gutwin.</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">224 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">Computational prediction of coiled-coil interaction structure specificity</dim:field>
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   	&lt;Title>Computational prediction of coiled-coil interaction structure specificity&lt;/Title>
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   	&lt;PublicationDate>2009&lt;/PublicationDate>
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        	&lt;DisplayName>Gutwin, Karl N. (Karl Nickolai)&lt;/DisplayName>
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   	&lt;Abstract>The alpha-helical coiled coil is a protein sequence and structural motif that consists of two or more helices in a parallel or antiparallel orientation supercoiling around a central axis. Coiled coils have been observed in a wide range of protein families, and many studies have focused on their sequence and structural diversity over the past half-century. In particular, the observation that coiled coils can be involved in determining protein-protein interactions and protein architectures has prompted the developments of methods to predict the structure of a coiled-coil complex from sequence information alone. In this thesis, I discuss the development of a structurally annotated database of coiled-coil sequence useful for training statistics-based methods of coiled-coil structure prediction. This database was used to retrain and stringently cross-validate the Multicoil method of predicting coiled-coil oligomerization state. In addition, I describe recent work using implicit and explicit structure models to predict dimeric coiled-coil orientation and alignment. Improvements to existing models, insight into coiled-coil structure determinants, and the future of coiled-coil prediction are also discussed.&lt;/Abstract>
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