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Improvements and extensions of a web-tool for finding candidate genes associated with rheumatoid arthritis
University of Skövde, School of Humanities and Informatics.
2005 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

QuantitativeTraitLocus (QTL) is a statistical method used to restrict genomic regions contributing to specific phenotypes. To further localize genes in such regions a web tool called “Candidate Gene Capture” (CGC) was developed by Andersson et al. (2005). The CGC tool was based on the textual description of genes defined in the human phenotype database OMIM. Even though the CGC tool works well, the tool was limited by a number of inconsistencies in the underlying database structure, static web pages and some gene descriptions without properly defined function in the OMIM database. Hence, in this work the CGC tool was improved by redesigning its database structure, adding dynamic web pages and improving the prediction of unknown gene function by using exon analysis. The changes in database structure diminished the number of tables considerably, eliminated redundancies and made data retrieval more efficient. A new method for prediction of gene function was proposed, based on the assumption that similarity between exon sequences is associated with biochemical function. Using Blast with 20380 exon protein sequences and a threshold E-value of 0.01, 639 exon groups were obtained with an average of 11 exons per group. When estimating the functional similarity, it was found that on the average 72% of the exons in a group had at least one Gene Ontology (GO) term in common.

Place, publisher, year, edition, pages
Skövde: Institutionen för kommunikation och information , 2005.
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:his:diva-26OAI: oai:DiVA.org:his-26DiVA: diva2:2617
Presentation
(English)
Uppsok
fysik/kemi/matematik
Supervisors
Examiners
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2009-06-03

Open Access in DiVA

fulltext(837 kB)355 downloads
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125f32422f8181cd766a1f49be393f07e2a122ecadc1103d398fccb379af01daee414fe6
Type fulltextMimetype application/pdf

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School of Humanities and Informatics
Bioinformatics (Computational Biology)

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf