Divergence Measures for Dna Segmentation

نویسندگان

  • Daniel Nicorici
  • Jaakko Astola
چکیده

Entropy-based divergence measures have shown promising results in many areas of engineering and image processing. In this study, we use the Jensen-Shannon and Jensen-Rényi divergence measures for DNA segmentation. Based on these information theoretic measures and protein shape coded in DNA, we propose a new approach to the problem of finding the borders between coding and noncoding DNA regions. We find that Jensen-Rényi divergence together with an alphabet based on protein shape characteristics brings improvements in accuracy for DNA segmentation. Our results demonstrate that the proposed approach is highly accurate, in finding the borders between coding and noncoding regions, and requires no “prior training” on known data sets.

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تاریخ انتشار 2003