Modeling Conserved Structure Patterns for Functional Noncoding RNA

RNA regulation has been increasingly recognized as a potential and perhaps overlooked genetics of higher organisms. Noncoding RNAs (ncRNA) may play various catalytic and regulatory roles in the genetic operating system. Recent studies using comparative genomics and molecular genetics show evidence of the presence of varied ncRNAs. Unlike protein coding genes, there is a lack of comparable information or outstanding signal for ncRNAs. Traditional computational linguistics show limitations in modeling complicated secondary structures and prevent us from identifying structure-function relationships of ncRNAs. This paper presents a novel approach, based on a set of distance constraints, to model the predicted RNA secondary structures. Further, a filtering schema is presented to identify matched models for the queried secondary structures.