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

Simple item page
dc.contributor.advisorBaker, Erich J.
dc.contributor.authorBush, Stephen J.
dc.contributor.departmentBiomedical Studies.en
dc.contributor.otherBaylor University. Institute of Biomedical Studies.en
dc.date.accessioned2008-10-02T18:47:42Z
dc.date.accessioned2017-04-07T19:33:16Z
dc.date.available2008-10-02T18:47:42Z
dc.date.available2017-04-07T19:33:16Z
dc.date.copyright2008-08
dc.date.issued2008-10-02T18:47:42Z
dc.descriptionIncludes bibliographic references (p. 42-44)en
dc.description.abstractIdentification 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.en
dc.description.degreeB.S.en
dc.description.statementofresponsibilityby Stephen J. Bush.en
dc.format.extentviii, 44 p. : ill.en
dc.format.extent1072014 bytes
dc.format.extent2656503 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2104/5221
dc.language.isoen_USen
dc.rightsBaylor 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.en
dc.rights.accessrightsWorldwide accessen
dc.subjectBioinformatics.en
dc.subjectApplication software -- Development.en
dc.subjectHomology (Biology)en
dc.subjectProteins.en
dc.subjectBlast (Electronic resource)en
dc.titleAutomated sequence homology : using empirical correlations to create graph-based networks for the elucidation of protein relationships.en
dc.typeThesisen

Files

Collections

Baylor University