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Bioinformatics 2008 24(13):i6-i14; doi:10.1093/bioinformatics/btn170
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© 2008 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.

POIMs: positional oligomer importance matrices—understanding support vector machine-based signal detectors

Sören Sonnenburg 1,{dagger},*, Alexander Zien 1,2,3,{dagger}, Petra Philips 2 and Gunnar Rätsch 2

1Fraunhofer Institute FIRST, Department IDA, Kekulèstr. 7, 12489 Berlin, 2Friedrich Miescher Laboratory, Max Planck Society, Spemannstr. 39 and 3Max Planck Institute for Biological Cybernetics, Spemannstr. 38, 72076 Tübingen, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: At the heart of many important bioinformatics problems, such as gene finding and function prediction, is the classification of biological sequences. Frequently the most accurate classifiers are obtained by training support vector machines (SVMs) with complex sequence kernels. However, a cumbersome shortcoming of SVMs is that their learned decision rules are very hard to understand for humans and cannot easily be related to biological facts.

Results: To make SVM-based sequence classifiers more accessible and profitable, we introduce the concept of positional oligomer importance matrices (POIMs) and propose an efficient algorithm for their computation. In contrast to the raw SVM feature weighting, POIMs take the underlying correlation structure of k-mer features induced by overlaps of related k-mers into account. POIMs can be seen as a powerful generalization of sequence logos: they allow to capture and visualize sequence patterns that are relevant for the investigated biological phenomena.

Availability: All source code, datasets, tables and figures are available at http://www.fml.tuebingen.mpg.de/raetsch/projects/POIM.

Contact: Soeren.Sonnenburg{at}first.fraunhofer.de

Supplementary information: Supplementary data are available at Bioinformatics online.

{dagger}The authors wish to be known that, in their opinion, the first two authors should be regarded as joint First Authors.


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