In silicoidentification of non-coding RNAs inHalobacterium salinarum NRC-1, a model archeon organism

Abstract

AbstractBackgroundIn addition to the regulatory elements already known, for instance, transcription factors or post-translation modifications, there is growing interest in the regulatory role played by non-coding RNA molecules (ncRNA), whose functions are performed at a different level of biological information processing. Model organisms provide a convenient way of working in the laboratory, and different research groups use these models to conduct studies on the cellular mechanisms present in these organisms. Although some ncRNAs elements have been found in theHalobacterium salinarummodel organism, we believe that not enough is known about these genomic regions.MethodsTherefore, anin silicoanalysis for ncRNA identification was conducted onH. salinarumNRC-1. Considering a data integration perspective and some available methodologies, several machine learning models were built and used to designate candidate ncRNAs genome regions.ResultsA total of 42 new ncRNAs were identified. Combing analysis with other available tools, it had been observed that some suggested candidates also was found with different methodologies and thus, it highlights the proposed results.