GlimmerHMM 3.0.4 – Eukaryotic Gene Finder based on GHMM

GlimmerHMM 3.0.4

:: DESCRIPTION

GlimmerHMM is a new gene finder based on a Generalized Hidden Markov Model (GHMM). Although the gene finder conforms to the overall mathematical framework of a GHMM, additionally it incorporates splice site models adapted from the GeneSplicer program and a decision tree adapted from GlimmerM. It also utilizes Interpolated Markov Models for the coding and noncoding models . Currently, GlimmerHMM’s GHMM structure includes introns of each phase, intergenic regions, and four types of exons (initial, internal, final, and single).

::DEVELOPER

the Center for Bioinformatics and Computational Biology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Sun Solaris / Alpha OSF1

:: DOWNLOAD

 GlimmerHMM

:: MORE INFORMATION

GlimmerHMM is OSI Certified Open Source Software .

Citation:

Majoros, W.H., Pertea, M., and Salzberg, S.L. TigrScan and GlimmerHMM: two open-source ab initio eukaryotic gene-finders Bioinformatics 20 2878-2879.

EuGène 4.2b – Gene Finder for Eukaryotic Organisms

EuGene 4.2b

:: DESCRIPTION

EuGene is an open gene finder for eukaryotic organisms. Compared to most existing gene finders, EuGene is characterized by its ability to simply integrate arbitrary sources of information in its prediction process. As most existing gene finders, EuGene can exploit probabilistic models like Markov models for discriminating coding from non coding sequences or to discriminate effective splice sites from false splice sites (using various mathematical models). Beyond this EuGene is able to integrate information from several signal (splice site, translation start…) prediction software, similarity with existing sequences (EST, mRNA, 5’/3′ EST from full length mRNA, proteins, genomic homologuous sequences) and output of existing gene finders… Based on all the available information, EuGene will output a prediction of maximal score i.e., maximally consistent with the information provided.

::DEVELOPER

EuGene team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Mac OsX

:: DOWNLOAD

EuGene

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2003 Jul 1;31(13):3742-5.
EUGENE’HOM: A generic similarity-based gene finder using multiple homologous sequences.
Foissac S, Bardou P, Moisan A, Cros MJ, Schiex T.

metaorf 1.0 – a very simple Gene Finder

metaorf 1.0

:: DESCRIPTION

metaorf is a very simple gene finder adapted for the fragmentary nature of metagenomic data. There is no advanced probabilistic model involved in this piece of software, it just looks for open reading frames, allowing (as specified by the user) sequences to start and end outside of the nucleotide reads.

::DEVELOPER

The Bengtsson-Palme Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX/ Windows
  • Perl

:: DOWNLOAD

 metaorf

:: MORE INFORMATION

BGF 1.01 – The Beijing Gene Finder

BGF 1.01

:: DESCRIPTION

BGF is a hidden Markov model (HMM) and dynamic programming based ab initio gene prediction program.

::DEVELOPER

BGI (Beijing Genomics Institute)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Heng Li, Jin-song Liu, Zhao Xu et al.,
Test Data Sets and Evaluation of Gene Prediction Programs on the Rice
J. Computer Science and Technology 2005, 20(4)

GeneZilla 1.22 – GHMM Eukaryotic Gene Finder

GeneZilla 1.22

:: DESCRIPTION

GeneZilla (formerly known as TIGRscan) is a state-of-the-art program for computational prediction of protein-coding genes in eukaryotic DNA, and is based on the Generalized Hidden Markov Model (GHMM) framework, similar to GENSCAN and GENIE. It is highly reconfigurable and includes software for retraining by the end-user. Graph-theoretic representations of the high scoring open reading frames are provided, allowing for exploration of sub-optimal gene models. It utilizes Interpolated Markov Models (IMMs), Maximal Dependence Decomposition (MDD), and includes states for signal peptides, branch points, TATA boxes, CAP sites, and will soon model CpG islands as well.

::DEVELOPER

Bill Majoros, now at Duke University.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac OsX

:: DOWNLOAD

GeneZilla

:: MORE INFORMATION

GeneZilla is available for download as OSI Certified Open Source Software under the Artistic License.

Citation:

Majoros W, et al. (2004) TIGRscan and GlimmerHMM: two open-source ab initio eukaryotic gene findersBioinformatics 20, 2878-2879.

CRITICA 1.05 – Microbial Gene Finder

CRITICA 1.05

:: DESCRIPTION

CRITICA (Coding Region Identification Tool Invoking Comparative Analysis) is a microbial gene finder that combines traditional approaches to the problem with a novel comparative analysis. If, in a nucleotide alignment, a pair of ORFs can be found in which the conceptual translated products are more conserved than would be expected from the amount of conservation at the nucleotide level, this is evolutionary evidence that the DNA sequences are protein coding. Regions found by this method are used to generate traditional dicodon frequencies for further analysis. CRITICA thus is not dependent on (often erroneous) sequence annotations, which many other algorithms base their training sets upon, and uses comparative information in a more biologically meaningful way than a simple similarity search. CRITICA was used in the Archeoglobus fulgidus and Aquifex aeolicus genome projects and is still in use by several groups

::DEVELOPER

Dr. Jonathan Badger

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 CRITICA

:: MORE INFORMATION

Citation:

Jonathan H. Badger, Gary J. Olsen.
CRITICA: Coding Region Identification Tool Invoking Comparative Analysis.
Molecular Biology and Evolution, 16(4):512-524. 1999.

TWAIN – Syntenic Gene Finder

TWAIN

:: DESCRIPTION

TWAIN is a software to predict genes simultaneously in two closely related eukaryotic organisms.TWAIN is a new syntenic genefinder which employs a Generalized Pair Hidden Markov Model (GPHMM) to predict genes in two closely related eukaryotic genomes simultaneously.It utilizes the MUMmer package to perform approximate alignment before applying a GPHMM based on an enhanced version of the TigrScan gene finder.

::DEVELOPER

Bill Majoros and Mihaela Pertea while at the J. Craig Venter Institute

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

TWAIN

:: MORE INFORMATION

Citation

Majoros W.H., Pertea M., Salzberg S.L. (2005) Efficient implementation of a Generalized Pair Hidden Markov Model for comparative gene findingBioinformatics 21 1782-1788.