Semantic subgroup discovery and cross-context linking for microarray data analysis

Authors:
Igor Mozetič;Nada Lavrač;Vid Podpečan;Petra Kralj Novak;Helena Motaln;Marko Petek;Kristina Gruden;Hannu Toivonen;Kimmo Kulovesi
Affiliations:
Jožef Stefan Institute, Ljubljana, Slovenia;Jožef Stefan Institute, Ljubljana, Slovenia, University of Nova Gorica, Nova Gorica, Slovenia;Jožef Stefan Institute, Ljubljana, Slovenia;Jožef Stefan Institute, Ljubljana, Slovenia;National Institute of Biology, Ljubljana, Slovenia;National Institute of Biology, Ljubljana, Slovenia;National Institute of Biology, Ljubljana, Slovenia;Department of Computer Science, University of Helsinki, Finland;Department of Computer Science, University of Helsinki, Finland
Venue:
Bisociative Knowledge Discovery
Year:
2012

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Abstract

The article 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. Contextualization and linking between highly diverse and distributed data and knowledge sources is therefore crucial for the implementation of bisociative reasoning. In the article 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 subgroup discovery. These genes are then contextualized by the computation of probabilistic links to diverse bioinformatics resources. Preliminary experiments with microarray data illustrate the approach.