Empirical Inference Conference Paper 1999

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

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
Bibtex Type: Conference Paper (inproceedings)
Event Place: Heidelberg, Germany
State: Published
Digital: 0
Electronic Archiving: grant_archive
Language: en
Organization: Max-Planck-Gesellschaft
Links:

BibTex

@inproceedings{5046,
  title = {Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites in DNA},
  booktitle = {German Conference on Bioinformatics  (GCB 1999)},
  abstract = {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. },
  organization = {Max-Planck-Gesellschaft},
  month = oct,
  year = {1999},
  slug = {5046},
  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.},
  month_numeric = {10}
}