GS-LAGE – Gene-specific Analysis of Microarray Global Data

GS-LAGE

:: DESCRIPTION

GS-LAGE (Gene Specific Large-scale Analysis of Gene Expression) is a global analysis strategy for large-scale microarray datasets integrated from public databases such as NCBI GEO.

::DEVELOPER

Lab of Bioinformatics and Molecular Design

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Jul 15;26(14):1723-30. doi: 10.1093/bioinformatics/btq279.
Global analysis of microarray data reveals intrinsic properties in gene expression and tissue selectivity.
Kim C1, Choi J, Park H, Park Y, Park J, Park T, Cho K, Yang Y, Yoon S.

ShortStack 3.8.5 – Comprehensive Annotation and Quantification of small RNA genes

ShortStack 3.8.5

:: DESCRIPTION

ShortStack is a tool developed to process and analyze smallRNA-seq data with respect to a reference genome, and output a comprehensive and informative annotation of all discovered small RNA genes.

::DEVELOPER

Axtell Lab @ Penn State

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

ShortStack

:: MORE INFORMATION

Citation:

Axtell MJ.
ShortStack: comprehensive annotation and quantification of small RNA genes.
RNA. 2013 Jun;19(6):740-51. doi: 10.1261/rna.035279.112. Epub 2013 Apr 22. PMID: 23610128; PMCID: PMC3683909.

DGIdb v2.22 – Rails Frontend to The Genome Institute’s Drug Gene Interaction Database

DGIdb v2.22

:: DESCRIPTION

The DGIdb (Drug-Gene Interaction database) mines existing resources that generate hypotheses about how mutated genes might be targeted therapeutically or prioritized for drug development.

::DEVELOPER

The Genome Institute at Washington University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX

:: DOWNLOAD

 DGIdb

:: MORE INFORMATION

Citation:

Nat Methods. 2013 Dec;10(12):1209-10. doi: 10.1038/nmeth.2689. Epub 2013 Oct 13.
DGIdb: mining the druggable genome.
Griffith M1, Griffith OL, Coffman AC, Weible JV, McMichael JF, Spies NC, Koval J, Das I, Callaway MB, Eldred JM, Miller CA, Subramanian J, Govindan R, Kumar RD, Bose R, Ding L, Walker JR, Larson DE, Dooling DJ, Smith SM, Ley TJ, Mardis ER, Wilson RK.

NU-IN 1.0.3 – Simulate Gene and Genome Evolution

NU-IN 1.0.3

:: DESCRIPTION

The NU-IN extension module is a extension to EvolSimulator. With the NU-IN module, users are now able to simulate both drift and selection at the nucleotide, amino acid, copy number, and gene family levels across sets of related genomes, for user-specified starting sequences and associated parameters.

::DEVELOPER

The Dlugosch Lab @ The University of Arizona

:: SCREENSHOTS

N/A

: REQUIREMENTS

:: DOWNLOAD

 NU-IN

:: MORE INFORMATION

Citation

BMC Res Notes. 2010 Aug 2;3:217. doi: 10.1186/1756-0500-3-217.
NU-IN: Nucleotide evolution and input module for the EvolSimulator genome simulation platform.
Dlugosch KM, Barker MS, Rieseberg LH.

NLR-parser 1.0 – Annotation Pipeline for NLR Genes

NLR-parser 1.0

:: DESCRIPTION

NLR-Parser is a tool to rapidly annotate the NLR (nucleotide-binding leucine-rich repeat) complement from sequenced plant genomes.

::DEVELOPER

NLR-parser team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • JRE
  • MEME suite

:: DOWNLOAD

 NLR-parser

:: MORE INFORMATION

Citation

NLR-parser: Rapid annotation of plant NLR complements.
Steuernagel B, Jupe F, Witek K, Jones JD, Wulff BB.
Bioinformatics. 2015 Jan 12. pii: btv005.

Gene Stacker 1.9 – Marker-assisted Gene Pyramiding

Gene Stacker 1.9

:: DESCRIPTION

Gene Stacker is a flexible open source tool for marker-assisted gene pyramiding. It can be used to construct efficient crossing schedules that gather desired alleles residing in multiple individuals into a single, specific target genotype (the so-called ideotype).

::DEVELOPER

Gene Stacker team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ MacOsX/Windows
  • Java

:: DOWNLOAD

 Gene Stacker

:: MORE INFORMATION

Citation

BMC Genet. 2015 Jan 30;16(1):2.
Heuristic exploitation of genetic structure in marker-assisted gene pyramiding problems.
Beukelaer H, Meyer G, Fack V.

GAP 0.0.1 – Gene functional Association Predictor

GAP 0.0.1

:: DESCRIPTION

GAP is an integrative, general-purpose framework for deriving a quantitative measure of gene similarity, which is relevant to a wide range of bioinformatics applications from gene clustering and phenotype and protein interactions predictions to interaction network modeling, and pharmacology analysis.

::DEVELOPER

Jurisica Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BMC Syst Biol. 2013 Mar 14;7:22. doi: 10.1186/1752-0509-7-22.
Novel semantic similarity measure improves an integrative approach to predicting gene functional associations.
Vafaee F, Rosu D, Broackes-Carter F, Jurisica I.

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

SPA3G 1.0 – Gene-centric Gene-Gene Interaction

SPA3G 1.0

:: DESCRIPTION

SPA3G implements the model-based kernel machine method for detecting gene-centric gene-gene interactions.

::DEVELOPER

Yuehua Cui, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux
  • R

:: DOWNLOAD

 SPA3G

:: MORE INFORMATION

Citation:

Li SY and YH Cui. (2012)
Gene-centric gene-gene interaction: a model-based kernel machine method.
Annals of Applied Statistics 6(3): 1134-1161.

CodingQuarry 2.0 – Fungal Gene Prediction

CodingQuarry 2.0

:: DESCRIPTION

CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts.

::DEVELOPER

Alison Testa: 13392554@student.curtin.edu.au

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler
:: DOWNLOAD

  CodingQuarry

:: MORE INFORMATION

Citation

BMC Genomics. 2015 Dec;16(1):1344. doi: 10.1186/s12864-015-1344-4. Epub 2015 Mar 11.
CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.
Testa AC1, Hane JK, Ellwood SR, Oliver RP.