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Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites (2000)  (Make Corrections)  (28 citations)
A. Zien, G. Ratsch, S. Mika, B. Scholkopf, T. Lengauer, K.-R. Muller
BIOINF: Bioinformatics



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Abstract: 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... (Update)

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BibTeX entry:   (Update)

A. Zien, G. Ratsch, S. Mika, B. Scholkopf, C. Lemmen, A. Smola, T. Lengauer, and K.R. Muller. Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics, page to appear, 2000. 17 http://citeseer.ist.psu.edu/zien00engineering.html   More

@article{ zien00engineering,
    author = "Zien and Ratsch and Mika and Scholkopf and Lengauer and Muller",
    title = "Engineering Support Vector Machine Kernels that Recognize Translation Initiation Sites",
    journal = "BIOINF: Bioinformatics",
    volume = "16",
    year = "2000",
    url = "citeseer.ist.psu.edu/zien00engineering.html" }
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40   Using the Fisher kernel method to detect remote protein homo.. - Jaakkola, Diekhans et al. - 1999
18   Identification of protein coding regions by database similar.. (context) - --, States - 1993
4   The ribosome scanning model for translation initiation: impl.. (context) - Agarwal, Bafna
4   Detecting non-adjoining correlations within signals in DNA (context) - Agarwal, Bafna
1   PairWise and SearchWise: finding the optimal alignment in a .. (context) - that, Birney et al. - 1996
1   and Zimmer (context) - Lengauer, Schneider et al. - 1989
1   A training algorithm for optimal margin classifiers (context) - Press, Guyon et al. - 1992



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