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Related Experiment Videos

S-SPatt: simple statistics for patterns on Markov chains.

Grégory Nuel1

  • 1Laboratoire Statistique et Génome 523 place des terrasses de l'Agora, 91000 Evry, France. spatt@genopole.cnrs.fr

Bioinformatics (Oxford, England)
|April 21, 2005
PubMed
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This study introduces S-SPatt, a tool for counting pattern occurrences in text files. It enables P-value computation for random Markovian sources using binomial approximation.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Text Analysis

Background:

  • Statistical analysis of biological sequences is crucial.
  • Identifying recurring patterns in biological texts aids understanding.
  • Markovian models are often used to represent sequence generation.

Purpose of the Study:

  • To present S-SPatt, a novel software tool.
  • To enable efficient counting of pattern occurrences in text files.
  • To facilitate statistical significance testing of observed patterns.

Main Methods:

  • S-SPatt software implementation.
  • Pattern counting algorithms for text files.
  • Binomial approximation for P-value calculation under Markovian assumptions.

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Main Results:

  • S-SPatt successfully counts pattern occurrences.
  • The tool computes P-values for observed patterns.
  • The binomial approximation provides a method for assessing significance.

Conclusions:

  • S-SPatt offers a practical solution for pattern analysis in text.
  • The software aids in the statistical evaluation of sequence patterns.
  • This approach is valuable for analyzing data from random Markovian sources.