Source:http://linkedlifedata.com/resource/pubmed/id/21297230
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
4
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| pubmed:dateCreated |
2011-2-7
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| pubmed:abstractText |
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.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:status |
MEDLINE
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| pubmed:issn |
1756-0756
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
3
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
311-33
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| pubmed:meshHeading | |
| pubmed:year |
2010
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| pubmed:articleTitle |
Fuzzy-adaptive-thresholding-based exon prediction.
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| pubmed:affiliation |
Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA. ankitag@eecs.northwestern.edu
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| pubmed:publicationType |
Journal Article
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