01978oam 2200409zu 450 991014678950332120210807000234.01-5090-9661-2(CKB)1000000000022777(SSID)ssj0000454420(PQKBManifestationID)12155056(PQKBTitleCode)TC0000454420(PQKBWorkID)10397897(PQKB)11628573(NjHacI)991000000000022777(EXLCZ)99100000000002277720160829d2005 uy engur|||||||||||txtccr2005 IEEE/SP 13th Workshop on Statistical Signal Processing[Place of publication not identified]I E E E20051 online resource (1358 pages) illustrationsBibliographic Level Mode of Issuance: Monograph0-7803-9403-8 Non-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.Signal processingCongressesSignal processing621.3822IEEE Signal Processing Society,PQKBPROCEEDING99101467895033212005 IEEE2494957UNINA