Incorporating diverse data to improve genetic network alignment with IsoRank

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2011

Author dc:creator

• Eisner, Eric David

Advisor dc:contributor.advisor

• Bonnie Berger.

• Electrical Engineering and Computer Science.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/77068

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/77068