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Bioinformatics Vol. 16 no. 9 2000
Pages 799-807
© 2000 Oxford University Press

Engineering support vector machine kernels that recognize translation initiation sites

A. Zien 1,, G. Rätsch 2, S. Mika 2, B. Schölkopf 3, T. Lengauer 1 and K.-R. Müller 2

1 GMD.SCAI, Schloss Birlinghoven, 53754 Sankt Augustin, Germany
2 GMD.FIRST, Kekuléstraße 7, 12489 Berlin, Germany
3 Microsoft Research, 1 Guildhall Street, Cambridge CB2 3NH, UK

Received on December 17, 1999 ; revised on March 22, 2000 ; accepted on March 29, 2000

Motivation: In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called translation initiation sites (TIS).

Results: The task of finding TIS can be modeled as a classification problem. We demonstrate the applicability of support vector machines for this task, and show how to incorporate prior biological knowledge by engineering an appropriate kernel function. With the described techniques the recognition performance can be improved by 26% over leading existing approaches. We provide evidence that existing related methods (e.g. ESTScan) could profit from advanced TIS recognition.

Contact: {Alexander.Zien,Gunnar.Raetsch,Sebastian. Mika}@gmd.de; bsc{at}microsoft.com

To whom correspondence should be addressed.


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