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Learning gene interactions from gene expression data dynamic Bayesian networks
University of Skövde, School of Humanities and Informatics.
2004 (English)Independent thesis Advanced level (degree of Master (One Year))Student thesis
Abstract [en]

Microarray experiments generate vast amounts of data that evidently reflect many aspects of the underlying biological processes. A major challenge in computational biology is to extract, from such data, significant information and knowledge about the complex interplay between genes/proteins. An analytical approach that has recently gained much interest is reverse engineering of genetic networks. This is a very challenging approach, primarily due to the dimensionality of the gene expression data (many genes, few time points) and the potentially low information content of the data. Bayesian networks (BNs) and its extension, dynamic Bayesian networks (DBNs) are statistical machine learning approaches that have become popular for reverse engineering. In the present study, a DBN learning algorithm was applied to gene expression data produced from experiments that aimed to study the etiology of necrotizing enterocolitis (NEC), a gastrointestinal inflammatory (GI) disease that is the most common GI emergency in neonates. The data sets were particularly challenging for the DBN learning algorithm in that they contain gene expression measurements for relatively few time points, between which the sampling intervals are long. The aim of this study was, therefore, to evaluate the applicability of DBNs when learning genetic networks for the NEC disease, i.e. from the above-mentioned data sets, and use biological knowledge to assess the hypothesized gene interactions. From the results, it was concluded that the NEC gene expression data sets were not informative enough for effective derivation of genetic networks for the NEC disease with DBNs and Bayesian learning.

Place, publisher, year, edition, pages
Skövde: Institutionen för kommunikation och information , 2004. , 113 p.
Keyword [en]
Dynamic Bayesiannetworks, genetic networks, gene expression data, reverse engineering, necrotizing enterocolitis
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-886OAI: oai:DiVA.org:his-886DiVA: diva2:3304
Presentation
(English)
Uppsok
Life Earth Science
Supervisors
Available from: 2008-02-18 Created: 2008-02-18 Last updated: 2010-02-09

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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