Non-coding RNA finding based on probabilistic secondary structure information
Non-coding RNAs (ncRNAs) are under intensive research focus since several years ago. Whereas many researches have done in this field since [1], not so much knowledge about ncRNAs are gained so far. One of the reasons for this is that there is not enough computational tools available for ncRNA analysis. ncRNA finding is one of the most important tools for the analysis. However, no viable solution is available so far in this area. Because finding ncRNA genes in a genomic sequence requires completely different methodology that taken for finding protein coding genes. The function of an RNA can be well inferred by its secondary structure. Therefore, in general, a family of functional RNAs share a common secondary structure. In order to find the common secondary structure, one can apply a secondary structure sensitive multiple alignment of RNAs, which can be done with profile SCFG. However, the multiple alignment requires the precise secondary structure of each RNA, which is, in many cases, not readily available. Even though there are many algorithms available for prediction of the secondary structure, they do not guarantee that their predictions are correct. Therefore, the multiple alignment is not always applicable especially in the early stage of the investigation of the target RNAs. In this poster, we propose a novel methodology to enable screening of the target RNAs in a genomic sequence without knowing their correct secondary structure.