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   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Bonnie Berger.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Bradley, Philip H. (Philip Harlan), 1973-</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Mathematics.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Mathematics</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2005-08-23T21:57:05Z</dim:field>
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   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2001.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (leaves 129-137).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">In this thesis, two algorithms for protein structural motif recognition are presented. A program is described which successfully recognizes the occurrence of the right-handed parallel 8-helix fold from protein sequence data alone. When run on sequences of unknown structure the program identifies the fold in a significant number of microbial outer membrane and cell-surface proteins implicated in infectious disease. A search algorithm is introduced for unsupervised discovery of protein sequence patterns that are significantly correlated with structural motifs. The algorithm identifies known, biologically relevant patterns as well as several potentially novel motifs. It is hoped that both algorithms may contribute to a better understanding of the connection between protein sequence and structure.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Philip H. Bradley.</dim:field>
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   <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>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Mathematics.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Mathematical methods for protein structural motif recognition</dim:field>
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   	&lt;Title>Mathematical methods for protein structural motif recognition&lt;/Title>
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   	&lt;PublicationDate>2001&lt;/PublicationDate>
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   	&lt;Abstract>In this thesis, two algorithms for protein structural motif recognition are presented. A program is described which successfully recognizes the occurrence of the right-handed parallel 8-helix fold from protein sequence data alone. When run on sequences of unknown structure the program identifies the fold in a significant number of microbial outer membrane and cell-surface proteins implicated in infectious disease. A search algorithm is introduced for unsupervised discovery of protein sequence patterns that are significantly correlated with structural motifs. The algorithm identifies known, biologically relevant patterns as well as several potentially novel motifs. It is hoped that both algorithms may contribute to a better understanding of the connection between protein sequence and structure.&lt;/Abstract>
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