Sangam: A Confluence of Knowledge Streams

Automated sequence homology : using empirical correlations to create graph-based networks for the elucidation of protein relationships.

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dc.contributor Baker, Erich J.
dc.contributor Baylor University. Institute of Biomedical Studies.
dc.contributor Biomedical Studies.
dc.creator Bush, Stephen J.
dc.date 2008-10-02T18:47:42Z
dc.date 2008-10-02T18:47:42Z
dc.date 2008-08
dc.date 2008-10-02T18:47:42Z
dc.date.accessioned 2022-05-18T12:29:27Z
dc.date.available 2022-05-18T12:29:27Z
dc.identifier http://hdl.handle.net/2104/5221
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/31774
dc.description Includes bibliographic references (p. 42-44)
dc.description Identification of sequence homology has presented a formidable obstacle despite significant increases in both technological capability and detailed knowledge of genomes and proteomes. While PSI-BLAST remains the popular tool for the job, it often returns inaccurate results with unacceptable levels of false positives. In order to increase the sensitivity and accuracy of homology finding, we have developed a software application called Automated Sequence Homology that bypasses these shortcomings and provides reliable and precise results. The system presented here is based upon the creation of a graph-based network highlighting the relational connections between proteins using empirical correlations. It takes a step back from PSI-BLAST to the acclaimed BLAST algorithm to create a sampling of the protein relational network.
dc.description by Stephen J. Bush.
dc.description B.S.
dc.format viii, 44 p. : ill.
dc.format 1072014 bytes
dc.format 2656503 bytes
dc.format application/pdf
dc.format application/pdf
dc.format application/pdf
dc.format application/pdf
dc.language en_US
dc.rights Baylor University 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. Contact librarywebmaster@baylor.edu for inquiries about permission.
dc.rights Worldwide access
dc.subject Bioinformatics.
dc.subject Application software -- Development.
dc.subject Homology (Biology)
dc.subject Proteins.
dc.subject Blast (Electronic resource)
dc.title Automated sequence homology : using empirical correlations to create graph-based networks for the elucidation of protein relationships.
dc.type Thesis


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