Prediction of human microRNA hairpins using only positive sample learning
نویسندگان
چکیده
منابع مشابه
Prediction of human microRNA hairpins using only positive sample learning
MicroRNAs (miRNAs) are small molecular non-coding RNAs that have important roles in the post-transcriptional mechanism of animals and plants. They are commonly 21-25 nucleotides (nt) long and derived from 60-90 nt RNA hairpin structures, called miRNA hairpins. A larger number of sequence segments in the human genome have been computationally identified with such 60-90 nt hairpins, however the m...
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15 صفحه اولPSoL: a positive sample only learning algorithm for finding non-coding RNA genes
MOTIVATION Small non-coding RNA (ncRNA) genes play important regulatory roles in a variety of cellular processes. However, detection of ncRNA genes is a great challenge to both experimental and computational approaches. In this study, we describe a new approach called positive sample only learning (PSoL) to predict ncRNA genes in the Escherichia coli genome. Although PSoL is a machine learning ...
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microRNAs (miRNAs) are 20-22 nt noncoding RNAs which are rapidly emerging as crucial regulators of gene expression in plants and animals. Identification of the hairpins which yield mature miRNAs is the first and most challenging step in miRNA gene prediction. We believe this step can best be achieved with biologically motivated feature design and classification techniques which account for the ...
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ژورنال
عنوان ژورنال: Journal of Biomedical Science and Engineering
سال: 2008
ISSN: 1937-6871,1937-688X
DOI: 10.4236/jbise.2008.12023