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GenRGenS specifications


Unique identifier OMICS_20902
Name GenRGenS
Software type Application/Script
Interface Command line interface, Graphical user interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Java
License GNU General Public License version 3.0
Computer skills Advanced
Version 2.1
Stability Stable
Source code URL
Maintained Yes




No version available



  • person_outline Alain Denise

Additional information

Publication for GenRGenS

GenRGenS citations


C PAmP: Large Scale Analysis and Database Construction Containing High Scoring Computationally Predicted Antimicrobial Peptides for All the Available Plant Species

PLoS One
PMCID: 3823563
PMID: 24244550
DOI: 10.1371/journal.pone.0079728

[…] no acid sequences following the amino acid distribution of UniProt/SwissProt. The former type of sequences was selected using BioPython whereas the latter two types of sequences were generated using GenRGenS . We used a diverse training set to avoid overfitting the classifier. The initial negative dataset consisted of 4,000 sequences (2,000 random protein fragments and 2,000 artificial sequences, […]


Selection on codon bias in yeast: a transcriptional hypothesis

Nucleic Acids Res
PMCID: 3814355
PMID: 23945943
DOI: 10.1093/nar/gkt740

[…] n Index (CAI), Frequency of optimal codons (Fop), Effective numbers of codons (Nc) and Codon Bias Index (CBI). Simulated sequences with specific codon usage or nucleotide content were generated using GenRGenS software (version 2.0) (). Three-base periodicity index (Pi) was computed using the formula elsewhere reported in detail (). In general, to extract, process, simulate and analyze data and seq […]


Ambushing the ambush hypothesis: predicting and evaluating off frame codon frequencies in Prokaryotic Genomes

BMC Genomics
PMCID: 3700767
PMID: 23799949
DOI: 10.1186/1471-2164-14-418

[…] intain the same coding properties of the original genome. To generate the randomized genomes they used both second-order and fifth-order, 3-periodic Markov models implemented in the MARKOV package of GenRGenS [,]. These models generate random genomes that preserve the dinucleotide or pentanucleotide frequencies of the original genome respectively.Tse et al. [] report a significant excess of OSCs w […]


BiDaS: a web based Monte Carlo BioData Simulator based on sequence/feature characteristics

Nucleic Acids Res
PMCID: 3692108
PMID: 23716644
DOI: 10.1093/nar/gkt420

[…] ce, while shorter sequences cannot be examined, as the model performs sequence analysis according to long-range correlations. In addition, several stand-alone applications have been developed such as GenRGenS () and rMotifGen () that generate sequences based on Monte Carlo simulation theory. However, no web service is available for these implementations, and the user has to download and install th […]


Cross kingdom sequence similarities between human micro RNAs and plant viruses

PMCID: 3821693
PMID: 24228136
DOI: 10.4161/cib.24951

[…] or studies of four specific crop plants (tobacco, potato, pepper and cowpea) for which there were only incomplete viral genomes available. Finally, we performed a statistical analysis on the results. GenRGens software was utilized to randomly generate genomics sequences. We created randomized versions of every single plant virus genome in the DPV database. The settings used were the Markov model, […]


BRASERO: A Resource for Benchmarking RNA Secondary Structure Comparison Algorithms

Adv Bioinformatics
PMCID: 3366197
PMID: 22675348
DOI: 10.1155/2012/893048

[…] ariations, both in terms of structure and length. To generate sequences of the negative set F, we use several sources: viral genomes (from the NCBI Viral Genome Resource) [], ENCODE sequences [], and GenRGenS, a generator of random structured sequences []. The BRASERO website contains also a documentation on the file formats of a benchmark and the required steps to design a benchmark. […]


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GenRGenS institution(s)
LRI, UMR CNRS 8623, Université Paris-Sud 11, Orsay, France; IGM, UMR CNRS 8621, Université Paris-Sud 11, Orsay, France
GenRGenS funding source(s)
Partially supported by the French IMPG and ‘ACI IMPBio’ programs, and the CNRS Specific Action ‘Modélisation et Algorithmique des Structures d’ARN’.

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