@article{BischlerKopfVoss2014,
  author    = {Bischler, Thorsten and Kopf, Matthias and Voss, Bjoern},
  title     = {Transcript mapping based on dRNA-seq data},
  series = {BMC Bioinformatics},
  volume    = {15},
  journal   = {BMC Bioinformatics},
  number    = {122},
  issn      = {1471-2105},
  doi       = {10.1186/1471-2105-15-122},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-116663},
  year      = {2014},
  abstract  = {Background: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems. Results: We present RNASEG, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori. Conclusions: With our algorithm it is possible to identify operons and 5'- and 3'-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics.},
  language  = {en}
}