Bisociative knowledge discovery for microarray data analysis

Mozetic , I , Lavrac , N , Podpecan , V , Novak , P K , Motaln , H , Petek , M , Gruden , K , Toivonen , H & Kulovesi , K 2010 , ' Bisociative knowledge discovery for microarray data analysis ' , pp. 190-199
Source: OAI

ABSTRACT The paper presents an approach to computational knowledge discovery through the mechanism of bisociation. Bisociative reasoning is at the heart of creative, accidental discovery (e.g., serendipity), and is focused on finding unexpected links by crossing contexts. Contextu- alization and linking between highly diverse and distributed data and knowledge sources is therefore crucial for the implementation of bisocia- tive reasoning. In the paper we explore these ideas on the problem of analysis of microarray data. We show how enriched gene sets are found by using ontology information as background knowledge in semantic sub- group discovery. These genes are then contextualized by the computation of probabilistic links to diverse bioinformatics resources. Preliminary ex- periments with microarray data illustrate the approach.


Available from: Petra Kralj Novak, May 30, 2015
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