MED 2.1 – Gene Prediction in Prokaryotic Genomes with Multivariate Entropy Distance method

MED 2.1

:: DESCRIPTION

MED is a non-supervised prokaryotic gene prediction method which integrates MED2.0 and TriTISA, an iterative self-learning translation initiation site (TIS) prediction algorithm. As the update of MED2.0, MED 2.1 modifies the TIS model by replacing the previous one to TriTISA, which imoroves the prediction accuracies for both 3′ and 5′ ends.

::DEVELOPER

ZhuLab, Peking Uiniversity, Beijing

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows

:: DOWNLOAD

 MED

:: MORE INFORMATION

Citation

Zhu,H.Q. et al. 2007
MED: a new non-supervised gene prediction algorithm forbacterial and archaeal genomes.
BMC Bioinformatics,8, 97

Gangqing,Hu. Et al. 2009.
Prediction of translation initiation site for microbial genomes with TriTISA.
Bioinformatics 25,123-125.

COLOMBO 4.0 / SIGI-HMM – Statistical Analysis of Sequences of a Genome /Prediction of Genomic Islands in Prokaryotic Genomes

COLOMBO 4.0

:: DESCRIPTION

COLOMBO is a software framework equipped with a GUI for the statistical analysis of sequences of a genome. It can be equipped with different plugins that actually perform the analysis. The current version of COLOMBO is supplied with SIGI-HMM, a tool for the prediction of Genomic Islands.

::DEVELOPER

Theoretical Computer Science and Algorithmic Methods , at the University of Göttingen.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Java
  • Perl

:: DOWNLOAD

COLOMBO

:: MORE INFORMATION

Citation

Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models.
Waack S, Keller O, Asper R, Brodag T, Damm C, Fricke WF, Surovcik K, Meinicke P, Merkl R.
BMC Bioinformatics. 2006 Mar 16;7:142.

GRC 1.0 – Annotation tool for Prokaryotic Genomes

GRC 1.0

:: DESCRIPTION

The GRC (Genome Reverse Compiler) is an annotation tool for prokaryotic genomes. Its name and philosophy are based on analogy with a high-level, programming language compiler.

::DEVELOPER

Andrew Warren

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Perl

:: DOWNLOAD

  GRC

:: MORE INFORMATION

Citation

The Genome Reverse Compiler: an explorative annotation tool.
Warren AS, Setubal JC.
BMC Bioinformatics. 2009 Jan 27;10:35. doi: 10.1186/1471-2105-10-35.

Genome Randomizer – Generate Random Sequences from Complete Prokaryotic Genomes

Genome Randomizer

:: DESCRIPTION

Genome Randomizer is a simple utility to generate random sequences from complete prokaryotic genomes using 11 different stochastic models.

::DEVELOPER

Computational Microbiology Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows
  • C++ Compiler

:: DOWNLOAD

 Genome Randomizer

:: MORE INFORMATION

Genome2D 3.1 – Visualization and Processing of Prokaryotic Genome

Genome2D 3.1

:: DESCRIPTION

Genome2D is a toolbox for visualization and processing of prokaryotic genome and transcriptome information

Genome2D Online Version

::DEVELOPER

Anne de Jong, Molecular Genetics, Linnaeusborg 7, University of Groningen

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 Genome2D

:: MORE INFORMATION

Citation

Genome2D: a visualization tool for the rapid analysis of bacterial transcriptome data.
Baerends R. J., Smits, W. K., de Jong, A., Hamoen, L. W., Kok, J. and Kuipers, O. P. (2004)
Genome Biol., 5, R37

GIDetector – Detect Genomic Islands in Prokaryotic Genomes

GIDetector

:: DESCRIPTION

GIDetector is a software that is used to detect genomic islands in prokaryotic genomes. GIDetector collects prokaryotic genome data from public websites based on users’ specification, analyzes genome features using multiple sources, including embedded third-party software Alien_hunter and REPuter, and predict genomic islands based on our trained models, which are decision-tree based ensemble classifiers.

::DEVELOPER

Che Lab of Bioinformatics at ESU

:: SCREENSHOTS

GIDetector

:: REQUIREMENTS

  • WIndowsJava

:: DOWNLOAD

 GIDetector

:: MORE INFORMATION

Citation

BMC Genomics. 2010 Nov 2;11 Suppl 2:S1. doi: 10.1186/1471-2164-11-S2-S1.
Classification of genomic islands using decision trees and their ensemble algorithms.
Che D, Hockenbury C, Marmelstein R, Rasheed K.

PGAAS 1.0 – Prokaryotic Genome Assembly Assistant System

PGAAS 1.0

:: DESCRIPTION

PGAAS is prokaryotic genome assembly assistant system. The approach upon which PGAAS is based is to confirm the order of contigs and fill gaps between contigs through peptide links obtained by searching each contig end with BLASTX against protein database.

::DEVELOPER

Center for Bioinformatics, PKU.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • MySQL
  • PHP
  • Apache

:: DOWNLOAD

 PGAAS

:: MORE INFORMATION

Citation:

PGAAS: a prokaryotic genome assembly assistant system.
Yu Z, Li T, Zhao J, Luo J.
Bioinformatics. 2002 May;18(5):661-5.

OxyGene 1.1.0 – Investigate Oxidative-response Genes in whole Prokaryotic Genomes

OxyGene 1.1.0

:: DESCRIPTION

OxyGene is an innovative platform that addresses exploration and comparative analysis of oxidative stress subsystems in prokaryotic whole genomes. OxyGene integrates an original annotation database, called OxyDB, holding thoroughly tested signatures and a new ontology for ab initio detection of ROS/RNS response genes. Data can be downloaded and viewed using an intuitive graphic user-friendly interface that contains tabular, graphical and text tools.

::DEVELOPER

B@SIC (Bioinformatics Applied to Stresses and Cellular Interactions)

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Mac / Linux
  • Java

:: DOWNLOAD

 OxyGene

:: MORE INFORMATION

Citation

David Thybert , Stéphane Avner , Céline Lucchetti-Miganeh , Angélique Chéron and Frédérique Barloy-Huble
OxyGene: an innovative platform for investigating oxidative-response genes in whole prokaryotic genomes
BMC Genomics 2008, 9:637

Gecko 2.0 – Gene Cluster Detection in Prokaryotic Genomes

Gecko 2.0

:: DESCRIPTION

Gecko is a further development of the original Gecko software. It allows for the systematic detection of gene cluster conservation in a large number of genomes. The enhancement over the original Gecko tool is the use of set-distance based gene cluster models that allow for the detection of gene clusters with diverse conservation patterns including gaps and missing genes in cluster occurrences. It is also tolerant of errors in gene homology assignment.

::DEVELOPER

Katharina Jahn and Leon Kuchenbecker

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Mac / Windows
  • Java

:: DOWNLOAD

Gecko

:: MORE INFORMATION

Citation

Computation of median gene clusters
S. Böcker, K. Jahn, J. Mixtacki, and J. Stoye. J. Comp. Biol., 16(8):1085-1099, 2009.