Rp-Bp statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.


Citations per year

Citations chart

Popular tool citations

chevron_left Translated ORF prediction chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

Rp-Bp specifications


Unique identifier OMICS_20323
Name Rp-Bp
Alternative name Ribosome profiling with Bayesian predictions
Software type Application/Script
Interface Command line interface
Restrictions to use None
Output data The predicted ORFs, as well as DNA and protein files containing the predicted sequences.
Output format BED, FASTA
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Version 1.1.9
Stability Stable
Maintained Yes



Add your version



  • person_outline Christoph Dieterich <>
  • person_outline Brandon Malone <>

Publication for Ribosome profiling with Bayesian predictions

Rp-Bp in publications

PMCID: 4180933
PMID: 25265476
DOI: 10.1371/journal.pone.0108616

[…] interests: the authors have declared that no competing interests exist., conceived and designed the experiments: pkc sh tw sd. performed the experiments: pkc fg sh rk rp bp. analyzed the data: pkc tw sd. contributed reagents/materials/analysis tools: pkc db ajc heb ic gl lab. wrote the paper: pkc lab sd. liver biopsy specimens: fg rk lab. explant liver tissues: db […]

PMCID: 3757003
PMID: 24009746
DOI: 10.1371/journal.pone.0073309

[…] have declared that no competing interests exist., conceived and designed the experiments: vc vp sp ta. performed the experiments: vp rp rs sp. analyzed the data: vc vp rp rs sp. wrote the paper: vc rp bp ac ta. contributed new simulation tools: vc rs sp., a recent paper by daubechies et al. claims that two independent component analysis (ica) algorithms, infomax and fastica, which are widely […]

To access a full list of publications, you will need to upgrade to our premium service.

Rp-Bp institution(s)
Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, University of Heidelberg, Heidelberg, Germany; DZHK (German Centre for Cardiovascular Research), Partner site Heidelberg/Mannheim, Heidelberg, Germany; Max Plank Institute for the Biology of Ageing, Koln, Germany; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland; Faculty of Science, University of Basel, Basel, Switzerland
Rp-Bp funding source(s)
Supported by the Klaus Tschira Stiftung GmbH [00.219b.2013]; the Swiss National Science Foundation through the NCCR RNA & Disease, and the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 241985 (European Research Council “miRTurn”).

Rp-Bp reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review Rp-Bp