Title: Fuzzy-adaptive-thresholding-based exon prediction

Authors: Ankit Agrawal, Ankush Mittal, Rahul Jain, Raghav Takkar

Addresses: Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA. ' Department of Computer Science and Engineering, College of Engineering Roorkee, Uttarakhand 247667, India. ' Indian School of Business, Hyderabad, Andhra Pradesh 500032, India. ' Indian Institute of Management, Lucknow, Uttarpradesh 226013, India

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

Keywords: adaptive thresholding; exon prediction; fuzzy sets; fuzzy logic rules; gene; intron; nucleotide sequences; period-3 components; power spectral density; bioinformatics; Saccharomyces cerevisiae; Bakers yeast.

DOI: 10.1504/IJCBDD.2010.038395

International Journal of Computational Biology and Drug Design, 2010 Vol.3 No.4, pp.311 - 333

Published online: 04 Feb 2011 *

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