Prediction of MicroRNA Precursors Using Parsimonious Feature Sets
نویسندگان
چکیده
منابع مشابه
Prediction of MicroRNA Precursors Using Parsimonious Feature Sets
MicroRNAs (miRNAs) are a class of short noncoding RNAs that regulate gene expression through base pairing with messenger RNAs. Due to the interest in studying miRNA dysregulation in disease and limits of validated miRNA references, identification of novel miRNAs is a critical task. The performance of different models to predict novel miRNAs varies with the features chosen as predictors. However...
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MicroRNAs (miRNAs) are non-coding RNAs with approximately 22 nucleotides (nt) that are derived from precursor molecules. These precursor molecules or pre-miRNAs often fold into stem-loop hairpin structures. However, a large number of sequences with premiRNA-like hairpins can be found in genomes. It is a challenge to distinguish the real pre-miRNAs from other hairpin sequences with similar stem-...
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MicroRNAs play important roles in most biological processes, including cell proliferation, tissue differentiation, and embryonic development, among others. They originate from precursor transcripts (pre-miRNAs), which contain phylogenetically conserved stem-loop structures. An important bioinformatics problem is to distinguish the pre-miRNAs from pseudo pre-miRNAs that have similar stem-loop st...
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MicroRNA biogenesis occurs in several steps from their precursors having irregular hairpin structures. The highly variable architecture of these stem-and-loop structures, which have terminal loops of various sizes and diverse structure destabilizing motifs present in their stem sections, may strongly influence the process of microRNA liberation. In order to better understand this process, more ...
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ژورنال
عنوان ژورنال: Cancer Informatics
سال: 2014
ISSN: 1176-9351,1176-9351
DOI: 10.4137/cin.s13877