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Deriving Genetic Networks from Gene Expression Data and Prior Knowledge

<p>In this work three different approaches for deriving genetic association networks were tested. The three approaches were Pearson correlation, an algorithm based on the Boolean network approach and prior knowledge. Pearson correlation and the algorithm based on the Boolean network approach derived associations from gene expression data. In the third approach, prior knowledge from a known genetic network of a related organism was used to derive associations for the target organism, by using homolog matching and mapping the known genetic network to the related organism. The results indicate that the Pearson correlation approach gave the best results, but the prior knowledge approach seems to be the one most worth pursuing</p>

Identiferoai:union.ndltd.org:UPSALLA/oai:DiVA.org:his-589
Date January 2001
CreatorsLindlöf, Angelica
PublisherUniversity of Skövde, Department of Computer Science, Skövde : Institutionen för datavetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, text

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