Incorporating diverse data to improve genetic network alignment with IsoRank
Name
824730299-MIT.pdf
Description
Full printable version
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1.99 MB
Format
Adobe PDF
Checksum (MD5)
dbfa855329dc682907ef5fe2aaeb21d7
Author(s)
Eisner, Eric David
Advisor(s)
Bonnie Berger.
Date Issued
2011
Publisher
Massachusetts Institute of Technology
Abstract
To more accurately predict which genes from different species have the same function (orthologs), I extend the network-alignment algorithm IsoRank to simultaneously align multiple unrelated networks over the same set of nodes. In addition to the original protein-interaction networks, I align genetic-interaction networks, gene-expression correlations, and chromosome localization data to improve the functional similarity of aligned genes. Alignments are evaluated with consistency measurements of protein function within ortholog clusters, and with an information-retrieval statistic from a small set of known orthologs. Integrating these additional types of data is shown to improve IsoRank's predictions of classes of genes that have sparse coverage in the original protein-interaction networks.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 26).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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