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Local Renyi entropic profiles of DNA sequences

Overview of attention for article published in BMC Bioinformatics, October 2007
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Title
Local Renyi entropic profiles of DNA sequences
Published in
BMC Bioinformatics, October 2007
DOI 10.1186/1471-2105-8-393
Pubmed ID
Authors

Susana Vinga, Jonas S Almeida

Abstract

In a recent report the authors presented a new measure of continuous entropy for DNA sequences, which allows the estimation of their randomness level. The definition therein explored was based on the Rényi entropy of probability density estimation (pdf) using the Parzen's window method and applied to Chaos Game Representation/Universal Sequence Maps (CGR/USM). Subsequent work proposed a fractal pdf kernel as a more exact solution for the iterated map representation. This report extends the concepts of continuous entropy by defining DNA sequence entropic profiles using the new pdf estimations to refine the density estimation of motifs. The new methodology enables two results. On the one hand it shows that the entropic profiles are directly related with the statistical significance of motifs, allowing the study of under and over-representation of segments. On the other hand, by spanning the parameters of the kernel function it is possible to extract important information about the scale of each conserved DNA region. The computational applications, developed in Matlab m-code, the corresponding binary executables and additional material and examples are made publicly available at http://kdbio.inesc-id.pt/~svinga/ep/. The ability to detect local conservation from a scale-independent representation of symbolic sequences is particularly relevant for biological applications where conserved motifs occur in multiple, overlapping scales, with significant future applications in the recognition of foreign genomic material and inference of motif structures.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 4%
United States 2 4%
United Kingdom 2 4%
France 1 2%
Cyprus 1 2%
Portugal 1 2%
Denmark 1 2%
Mexico 1 2%
Russia 1 2%
Other 1 2%
Unknown 43 77%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 34%
Researcher 10 18%
Professor 7 13%
Professor > Associate Professor 5 9%
Other 2 4%
Other 6 11%
Unknown 7 13%
Readers by discipline Count As %
Computer Science 12 21%
Agricultural and Biological Sciences 11 20%
Biochemistry, Genetics and Molecular Biology 5 9%
Medicine and Dentistry 4 7%
Physics and Astronomy 3 5%
Other 13 23%
Unknown 8 14%