Related Experiment Video
Updated: Jul 9, 2026

Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat
Published on: September 20, 2016
Evolutionary optimization of sequence kernels for detection of bacterial gene starts
Britta Mersch1, Tobias Glasmachers, Peter Meinicke
1Abteilung Molekulare Biophysik, German Cancer Research Center, 69120 Heidelberg, Germany. b.mersch@dkfz.de
Abstract:
Oligo kernels for biological sequence classification have a high discriminative power. A new parameterization for the K-mer oligo kernel is presented, where all oligomers of length K are weighted individually. The task specific choice of these parameters increases the classification performance and reveals information about discriminative features. For adapting the multiple kernel parameters based on cross-validation the covariance matrix adaptation evolution strategy is proposed. It is applied to optimize the trimer oligo kernels for the detection of bacterial gene starts. The resulting kernels lead to higher classification rates, and the adapted parameters reveal the importance of particular triplets for classification, for example of those occurring in the Shine-Dalgarno Sequence.
More Related Videos
Related Concept Videos
Leaky Scanning
Evolutionary Relationships through Genome Comparisons
Gene Evolution - Fast or Slow?
In contrast, regions which code...
Gene Evolution - Fast or Slow?
In contrast, regions which code...
Modern Molecular Taxonomy
Evolution of Microbial Genome

