Apr 292015
 

nocoRNAc 1.23

:: DESCRIPTION

nocoRNAc (non-coding RNA characterization) is a Java program for the prediction and characterization of ncRNA transcripts in bacteria. nocoRNAc takes the coordinates of putative ncRNA loci as input and annotates them with transcriptional features to conduct strand-specific transcript predictions. Our approach is not limited to intergenic regions but also applied to predict cis-encoded asRNA transcripts. For the detection of the transcript’s 3′ end nocoRNAc integrates the program TransTermHP (Kingsford et al., 2007) to predict Rho-independent terminator signals. The 5′ start is predicted by the detection of destabilized regions in the genomic DNA. For this purpose we implemented the so-called SIDD model (Benham, Bi, 2004), which has been shown to be applicable to the detection of promoter regions in microbial genomes. Therefore, nocoRNAc does not have to rely on information about known TFBS. The putative transcriptional features are then combined to classify ncRNA loci into either being an ncRNA transcript or not. For ncRNAs that are classified as transcripts the strand is automatically specified, and its boundaries are derived from the SIDD sites and the Rho-independent transcription termination signal. Those loci that are classified not to be a transcript might be false positive predictions or they contain cis-regulatory motifs. For the latter, nocoRNAc incorporates other functionalities for the further analysis of the ncRNA loci such as the search for known RNA motifs from the Rfam database. Furthermore, nocoRNAc provides methods for the prediction of RNA-RNA interactions between ncRNAs and mRNAs. All results can be studied in detail in nocoRNAc’s integrated interactive R environment.

::DEVELOPER

Research Group “Integrative Transcriptomics” , Center for Bioinformatics Tübingen, University of Tübingen

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

nocoRNAc

:: MORE INFORMATION

Citation

nocoRNAc: Characterization of non-coding RNAs in prokaryotes
Alexander Herbig, Kay Nieselt
BMC Bioinformatics. 2011 Jan 31;12:40. doi: 10.1186/1471-2105-12-40.

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