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100   $a20160829d2005      uy 
101 0 $aeng
135   $aur|||||||||||
181   $ctxt
182   $cc
183   $acr
200 00$a2005 IEEE/SP 13th Workshop on Statistical Signal Processing
210 31$a[Place of publication not identified]$cI E E E$d2005
215   $a1 online resource (1358 pages) $cillustrations
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a0-7803-9403-8 
330   $aNon-coding RNAs (ncRNA) are RNA molecules that function in the cells without being translated into proteins. In recent years, much evidence has been found that ncRNAs play a crucial role in various biological processes. As a result, there has been an increasing interest in the prediction of ncRNA genes. Due to the conserved secondary structure in ncRNAs, there exist pairwise dependencies between distant bases. These dependencies cannot be effectively modeled using traditional HMMs, and we need a more complex model such as the context-sensitive HMM (csHMM). In this paper, we overview the role of csHMMs in the RNA secondary structure analysis and the prediction of ncRNA genes. It is demonstrated that the context-sensitive HMMs can serve as an efficient framework for these purposes.
606   $aSignal processing$vCongresses
615  0$aSignal processing
676   $a621.3822
712 02$aIEEE Signal Processing Society,
801  0$bPQKB
906   $aPROCEEDING
912   $a9910146789503321
996   $a2005 IEEE$92494957
997   $aUNINA