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Bioinformatics 2009 25(12):i145-i153; doi:10.1093/bioinformatics/btp215
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Probabilistic retrieval and visualization of biologically relevant microarray experiments

José Caldas 1,*, Nils Gehlenborg 2,3, Ali Faisal 1, Alvis Brazma 2 and Samuel Kaski 1

1Helsinki Institute for Information Technology, Department of Information and Computer Science, Helsinki University of Technology, Finland, 2Microarray Team, European Bioinformatics Institute and 3Graduate School of Life Sciences, University of Cambridge, Cambridge, UK

*To whom correspondence should be addressed.


  Abstract

Motivation: As ArrayExpress and other repositories of genome-wide experiments are reaching a mature size, it is becoming more meaningful to search for related experiments, given a particular study. We introduce methods that allow for the search to be based upon measurement data, instead of the more customary annotation data. The goal is to retrieve experiments in which the same biological processes are activated. This can be due either to experiments targeting the same biological question, or to as yet unknown relationships.

Results: We use a combination of existing and new probabilistic machine learning techniques to extract information about the biological processes differentially activated in each experiment, to retrieve earlier experiments where the same processes are activated and to visualize and interpret the retrieval results. Case studies on a subset of ArrayExpress show that, with a sufficient amount of data, our method indeed finds experiments relevant to particular biological questions. Results can be interpreted in terms of biological processes using the visualization techniques.

Availability: The code is available from http://www.cis.hut.fi/projects/mi/software/ismb09.

Contact: jose.caldas{at}tkk.fi


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