Using a bioinformatics approach to identify genes that have possible candidacy of association with retinitis pigmentosa: GeneWeaver

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dc.contributor.advisorBaker, Erich J.
dc.contributor.authorLie, Natasha
dc.contributor.departmentBiochemistry.en_US
dc.contributor.schoolsHonors College.en_US
dc.date.accessioned2016-08-10T16:10:11Z
dc.date.available2016-08-10T16:10:11Z
dc.date.copyright2016-05-27
dc.date.issued2016-08-10
dc.description.abstractRetinitis pigmentosa (RP) is a retinal degenerative disorder that affects about 1 in 3,000 people. The disease is genetic in cause, and currently there is no cure. The genetic cause of the disease may be contributed to one of several different genes, underscoring the complex genetic underpinnings of this disease. The information required to determine which genes are potentially causative for RP may exist, but it is difficult to determine which genes are most suitable for study because of the immense wealth and breadth of available information. In other words, large-scale heterogeneous species-specific data often obfuscates the true causative genetic background of RP. In this study we describe a method of identifying genes that may contribute to RP using the bioinformatics techniques of graph theory and database utilization. We report a potential ranked list of genes in which disruptions are likely causative of RP.en_US
dc.identifier.urihttp://hdl.handle.net/2104/9733
dc.language.isoen_USen_US
dc.rightsBaylor University projects 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 libraryquestions@baylor.edu for inquiries about permission.en_US
dc.rights.accessrightsWorldwide accessen_US
dc.subjectGenetic diseases.en_US
dc.subjectGenetics.en_US
dc.subjectGeneWeaver.en_US
dc.subjectEye diseases.en_US
dc.subjectRetinitis pigmentosa.en_US
dc.subjectRetina.en_US
dc.subjectEye.en_US
dc.subjectBioinformatics.en_US
dc.subjectConvergent functional genomics.en_US
dc.subjectGraph theory.en_US
dc.subjectRare diseases.en_US
dc.titleUsing a bioinformatics approach to identify genes that have possible candidacy of association with retinitis pigmentosa: GeneWeaveren_US
dc.typeThesisen_US

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