A sequence-based filtering method for ncRNA identification and its application to searching for riboswitch elements
Author(s) -
Shaojie Zhang,
Ilya Borovok,
Yair Aharonowitz,
Roded Sharan,
Vineet Bafna
Publication year - 2006
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btl232
Subject(s) - riboswitch , non coding rna , computer science , computational biology , sequence (biology) , filter (signal processing) , rna , data mining , biology , gene , genetics , computer vision
Recent studies have uncovered an "RNA world", in which non coding RNA (ncRNA) sequences play a central role in the regulation of gene expression. Computational studies on ncRNA have been directed toward developing detection methods for ncRNAs. State-of-the-art methods for the problem, like covariance models, suffer from high computational cost, underscoring the need for efficient filtering approaches that can identify promising sequence segments and speedup the detection process.
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