Computational Methods for Identification of Human microRNA Precursors
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Nam:2004:PRICAI,
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author = "Jin-Wu Nam and Wha-Jin Lee and Byoung-Tak Zhang",
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title = "Computational Methods for Identification of Human
{microRNA} Precursors",
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booktitle = "8th Pacific Rim International Conference on Artificial
Intelligence, PRICAI 2004",
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year = "2004",
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editor = "Chengqi Zhang and Hans W. Guesgen and Wai-Kiang Yeap",
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volume = "3157",
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series = "Lecture Notes in Computer Science",
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address = "Auckland, New Zealand",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-540-22817-2",
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DOI = "doi:10.1007/978-3-540-28633-2_77",
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size = "10 pages",
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abstract = "MicroRNA (miRNA), one of non-coding RNAs (ncRNAs),
regulates gene expression directly by arresting the
messenger RNA (mRNA) translation, which is important
for identifying putative miRNAs. In this study, we
suggest a searching procedure for human miRNA
precursors using genetic programming that automatically
learn common structures of miRNAs from a set of known
miRNA precursors. Our method consists of three-steps.
At first, for each miRNA precursor, we adopted genetic
programming techniques to optimize the RNA
Common-Structural Grammar (RCSG) of populations until
certain fitness is achieved. In this step, the
specificity and the sensitivity of a RCSG for the
training data set were used as the fitness criteria.
Next, for each optimized RCSG, we collected candidates
of matching miRNA precursors with the corresponding
grammar from genome databases. Finally, we selected
miRNA precursors over a threshold (= 365) of scoring
model from the candidates. This step would reduce false
positives in the candidates. To validate the
effectiveness of our miRNA method, we evaluated the
learned RCSG and the scoring model with test data.
Here, we obtained satisfactory results, with high
specificity (= 51/64) and proper sensitivity (= 51/82)
using human miRNA precursors as a test data set.",
- }
Genetic Programming entries for
Jin-Wu Nam
Wha-Jin Lee
Byoung-Tak Zhang
Citations