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Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites in DNA

1999

Conference Paper

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In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points from which regions encoding pro­ teins start, the so­called translation initiation sites (TIS). This can be modeled as a classification prob­ lem. We demonstrate the power of support vector machines (SVMs) for this task, and show how to suc­ cessfully incorporate biological prior knowledge by engineering an appropriate kernel function.

Author(s): Zien, A. and Rätsch, G. and Mika, S. and Schölkopf, B. and Lemmen, C. and Smola, A. and Lengauer, T. and Müller, K-R.
Book Title: German Conference on Bioinformatics (GCB 1999)
Year: 1999
Month: October
Day: 0

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Place: Heidelberg, Germany

Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
State: Published

Links: Web

BibTex

@inproceedings{5046,
  title = {Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites in DNA},
  author = {Zien, A. and R{\"a}tsch, G. and Mika, S. and Sch{\"o}lkopf, B. and Lemmen, C. and Smola, A. and Lengauer, T. and M{\"u}ller, K-R.},
  booktitle = {German Conference on Bioinformatics  (GCB 1999)},
  organization = {Max-Planck-Gesellschaft},
  month = oct,
  year = {1999},
  doi = {},
  month_numeric = {10}
}