Fuzzy-adaptive-thresholding-based exon prediction

Ankit Agrawal*, Ankush Mittal, Rahul Jain, Raghav Takkar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Thresholding is always critical and decisive in many bioinformatics problems. In this paper, we propose and apply a fuzzy-logic-based adaptive thresholding approach to a well-known solution for the exon prediction problem, which uses a threshold on the frequency component at f = 1/3 in the nucleotide sequence. The proposed approach allows the thresholds to vary along the data set based on the local statistical properties. Experiments and results on the nucleotide data of Saccharomyces cerevisiae (Bakers yeast) illustrate the advantage of our approach. A user-friendly GUI in MATLAB is freely available for academic use at www.cs.iastate.edu/∼ankitag/ FATBEP.html.

Original languageEnglish (US)
Pages (from-to)311-333
Number of pages23
JournalInternational Journal of Computational Biology and Drug Design
Volume3
Issue number4
DOIs
StatePublished - 2010

Keywords

  • Adaptive thresholding
  • Exon
  • Fuzzy logic rules
  • Fuzzy sets
  • Gene
  • Intron
  • Nucleotide sequence
  • Period-3 component
  • Power spectral density

ASJC Scopus subject areas

  • Drug Discovery
  • Computer Science Applications

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