Refine
Has Fulltext
- yes (11)
Is part of the Bibliography
- yes (11)
Document Type
- Journal article (11)
Language
- English (11)
Keywords
- liraglutide (2)
- obesity (2)
- transcriptome (2)
- Campylobacter jejuni (1)
- FinO family (1)
- GLP-1 (1)
- HFQ (1)
- HGF (1)
- HNSCC (1)
- Met (1)
Institute
- Institut für Molekulare Infektionsbiologie (8)
- Theodor-Boveri-Institut für Biowissenschaften (3)
- Klinik und Poliklinik für Allgemein-, Viszeral-, Gefäß- und Kinderchirurgie (Chirurgische Klinik I) (2)
- Medizinische Klinik und Poliklinik I (2)
- Medizinische Klinik und Poliklinik II (2)
- Pathologisches Institut (2)
- Institut für Hygiene und Mikrobiologie (1)
- Institut für Klinische Neurobiologie (1)
- Institut für Virologie und Immunbiologie (1)
- Klinik und Poliklinik für Mund-, Kiefer- und Plastische Gesichtschirurgie (1)
Sonstige beteiligte Institutionen
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.