Tag: Prokaryote

YACOP 2 – Gene Prediction for Prokaryotes

YACOP 2

:: DESCRIPTION

YACOP is a metatool for gene prediction in prokaryotic genomes. The predictions generated by the tool are based on the output of existing gene finding programs. In present YACOP supports the boolean combination of predictions from Critica 105b (with wublast2), Glimmer 2.02 or Glimmer 2.10 (with RBSfinder), Orpheus (with dps) and ZCurve1.0. The output can be adapted to different modes by customizing the enclosed ini-file, so that the tool can also be used for comparision and evaluation of different predictions.

::DEVELOPER

the Department of Bioinformatics of the University of Göttingen

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

YACOP

:: MORE INFORMATION

Citation

M. Tech and R. Merkl (2003)
YACOP: Enhanced Gene Prediction Obtained by a Combination of Existing Methods
In Silico Biology 3:4.

BoBro 2.1 – Identifying cis Regulatory Motifs in Prokaryotes

BoBro 2.1

:: DESCRIPTION

BoBro (BOTTLENECK BROKEN TOOL) is a software  for prediction of cis-regulatory motifs in a given set of promoter sequences.

::DEVELOPER

Qin Ma  , Bioinformatic and Mathematical Biosciences Lab, The Ohio State University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOs/ Windows

:: DOWNLOAD

 BoBro

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Sep 15;29(18):2261-8. doi: 10.1093/bioinformatics/btt397. Epub 2013 Jul 10.
An integrated toolkit for accurate prediction and analysis of cis-regulatory motifs at a genome scale.
Ma Q1, Liu B, Zhou C, Yin Y, Li G, Xu Y.

Nucleic Acids Res. 2011 Apr;39(7):e42. Epub 2010 Dec 11.
A new framework for identifying cis-regulatory motifs in prokaryotes.
Li G, Liu B, Ma Q, Xu Y.

CNOGpro 1.1 – Copy Numbers of Genes in Prokaryotes

CNOGpro 1.1

:: DESCRIPTION

CNOGpro is a methods for assigning copy number states and breakpoints in resequencing experiments of prokaryotic organisms.

::DEVELOPER

Ola Brynildsrud <ola.brynildsrud at nmbu.no>, Lars-Gustav Snipen

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R

:: DOWNLOAD

 CNOGpro

:: MORE INFORMATION

Citation

Bioinformatics. 2015 Feb 1. pii: btv070.
CNOGpro: Detection and quantification of CNVs in prokaryotic whole-genome sequencing data.
Brynildsrud O, Snipen LG, Bohlin J

MetaGeneAnnotator – Gene Finding program for Prokaryote and Phage

MetaGeneAnnotator

:: DESCRIPTION

MetaGeneAnnotator is a prokaryotic gene finding program from environmental genome shotgun sequences or metagenomic sequences.

::DEVELOPER

Hideki Noguchi (hnoguchi @nig.ac.jp)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX

:: DOWNLOAD

MetaGeneAnnotator

:: MORE INFORMATION

Citation

MetaGeneAnnotator: detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes.
Noguchi H, Taniguchi T, Itoh T.
DNA Res. 2008 Dec;15(6):387-96. doi: 10.1093/dnares/dsn027.

Roary 3.13.0 – Prokaryote Pan Genome Analysis

Roary 3.13.0

:: DESCRIPTION

Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by Prokka (Seemann, 2014)) and calculates the pan genome.

::DEVELOPER

Roary team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /  MacOsX

:: DOWNLOAD

 Roary

:: MORE INFORMATION

Citation

Roary: rapid large-scale prokaryote pan genome analysis.
Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S, Holden MT, Fookes M, Falush D, Keane JA, Parkhill J.
Bioinformatics. 2015 Nov 15;31(22):3691-3. doi: 10.1093/bioinformatics/btv421.

EasyGene 1.2c – Prediction of Genes in Prokaryotes

EasyGene 1.2c

:: DESCRIPTION

EasyGene estimates the statistical significance of a predicted gene. The gene finder is based on a hidden Markov model (HMM) that is automatically estimated for a new genome. Using extensions of similarities in Swiss-Prot, a high quality training set of genes is automatically extracted from the genome and used to estimate the HMM. Putative genes are then scored with the HMM, and based on score and length of an ORF, the statistical significance is calculated. The measure of statistical significance for an ORF is the expected number of ORFs in one megabase of random sequence at the same significance level or better, where the random sequence has the same statistics as the genome in the sense of a third order Markov chain.

::DEVELOPER

DTU Health Tech

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

EasyGene

:: MORE INFORMATION

Citation

Large-scale prokaryotic gene prediction and comparison to genome annotation.
P. Nielsen and A. Krogh.
Bioinformatics: 21:4322-4329, 2005.

EasyGene – a prokaryotic gene finder that ranks ORFs by statistical significance.
Thomas Schou Larsen and Anders Krogh.
BMC Bioinformatics: 4:21, 2003