Tag: Gene Expression

MNI – Identify the Gene Targets of a Drug Treatment based on Gene-expression data

MNI

:: DESCRIPTION

The MNI (Mode-of-action by Network Inference ) is an algorithm to identify the gene targets of a drug treatment based on gene-expression data. In a typical use of the algorithm, a single expression profile, say obtained as a result of a treatment under study, is used as the test profile while a set of hundreds of expression profiles is used as the training set. The MNI algorithm uses the large training data set of expression profiles to construct a statistical model of gene-regulatory networks in a cell or tissue. The model describes combinatorial influences of genes on one another.

::DEVELOPER

di Bernardo Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • MatLab

:: DOWNLOAD

 MNI

:: MORE INFORMATION

Citation

Nat Protoc. 2006;1(6):2551-4.
The mode-of-action by network identification (MNI) algorithm: a network biology approach for molecular target identification.
Xing H, Gardner TS.

MSBE 1.0.5 – Analysis of Gene Expression data using a new bi-clustering method

MSBE 1.0.5

:: DESCRIPTION

MSBE is a tool for the analysis of gene expression data using a new bi-clustering method. It can find constant bi-clusters and additive bi-clusters.

::DEVELOPER

Lusheng Wang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux
  • Java

:: DOWNLOAD

  MSBE

:: MORE INFORMATION

Citation

Computing the maximum similarity bi-clusters of gene expression data.
Liu X, Wang L.
Bioinformatics. 2007 Jan 1;23(1):50-6.

GEDS – Gene Expression Display Server

GEDS

:: DESCRIPTION

GEDS is an integrative platform to show human gene expressions in cancer types, normal tissues and cell lines for user input genes, miRNAs and proteins.

::DEVELOPER

An-Yuan Guo’s Bioinformatics Laboratory

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Xia M, Liu CJ, Zhang Q, Guo AY.
GEDS: A Gene Expression Display Server for mRNAs, miRNAs and Proteins.
Cells. 2019 Jul 3;8(7):675. doi: 10.3390/cells8070675. PMID: 31277321; PMCID: PMC6678772.

ContextTRAP – Pathway based analysis of Gene Expression data

ContextTRAP

:: DESCRIPTION

ContextTRAP is novel approach for prioritizing pathways by utilizing both results from pathway analysis tools and the literature information.

::DEVELOPER

Bio & Health Informatics Lab , Seoul National University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Lee J, Jo K, Lee S, Kang J, Kim S.
Prioritizing biological pathways by recognizing context in time-series gene expression data.
BMC Bioinformatics. 2016 Dec 23;17(Suppl 17):477. doi: 10.1186/s12859-016-1335-8. PMID: 28155707; PMCID: PMC5259824.

rsgcc 1.0.6 – Gini methodology-based correlation and Clustering analysis of Microarray and RNA-Seq Gene Expression data

rsgcc 1.0.6

:: DESCRIPTION

rsgcc is an R package that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.

::DEVELOPER

Ma Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R package

:: DOWNLOAD

 rsgcc

:: MORE INFORMATION

Citation

Plant Physiol. 2012 Sep;160(1):192-203. doi: 10.1104/pp.112.201962. Epub 2012 Jul 13.
Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.
Ma C1, Wang X.

MRFSeq 0.1 – Gene Expression Analysis using Coexpression and RNA-Seq data

MRFSeq 0.1

:: DESCRIPTION

MRFSeq is a new efficient algorithm based on a Markov random field (MRF) model that uses additional gene coexpression data to enhance the prediction power.

::DEVELOPER

Ei-Wen Yang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • G++
  • R package

:: DOWNLOAD

 MRFSeq

:: MORE INFORMATION

Citation:

Bioinformatics. 2013 Sep 1;29(17):2153-61. doi: 10.1093/bioinformatics/btt363. Epub 2013 Jun 21.
Differential gene expression analysis using coexpression and RNA-Seq data.
Yang EW1, Girke T, Jiang T.

ChromoViz 1.1 – Visualization of Gene Expression data onto Chromosomes

ChromoViz 1.1

:: DESCRIPTION

ChromoViz is an R package for multimodal visualization of microarray data, DNA copy number alterations, cross-platform and cross-species comparisons,and genomic non-expression data obtained from public databases onto chromosomes.

::DEVELOPER

SNUBI

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R package

:: DOWNLOAD

 ChromoViz

:: MORE INFORMATION

Citation

Bioinformatics. 2004 May 1;20(7):1191-2. Epub 2004 Feb 5.
ChromoViz: multimodal visualization of gene expression data onto chromosomes using scalable vector graphics.
Kim J1, Chung HJ, Park CH, Park WY, Kim JH.

PathRanker 0.1 – Mining Metabolic Pathways through Gene Expression

PathRanker 0.1

:: DESCRIPTION

PathRanker is an R-package for extraction and analysis of the most active metabolic pathways through gene expression data.

::DEVELOPER

Timothy Hancock, PhD.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/Windows
  • R package

:: DOWNLOAD

  PathRanker

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Sep 1;26(17):2128-35. doi: 10.1093/bioinformatics/btq344. Epub 2010 Jun 29.
Mining metabolic pathways through gene expression.
Hancock T1, Takigawa I, Mamitsuka H.

ROS-DET – Robust Detector of Switching Mechanisms in Gene Expression

ROS-DET

:: DESCRIPTION

ROS-DET (standing for RObust Switching mechanisms DETector) is an efficient and robust method for detecting switching mechanisms in gene expression.

::DEVELOPER

Mitsunori, Kayano, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX

:: DOWNLOAD

 ROS-DET

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2011 Jun;39(11):e74. doi: 10.1093/nar/gkr130. Epub 2011 Apr 1.
ROS-DET: robust detector of switching mechanisms in gene expression.
Kayano M1, Takigawa I, Shiga M, Tsuda K, Mamitsuka H.

PennSeq – Isoform-specific Gene Expression Quantification in RNA-Seq

PennSeq

:: DESCRIPTION

PennSeq is a statistical method that allows each isoform to have its own non-uniform read distribution.

::DEVELOPER

Yu Hu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Perl

:: DOWNLOAD

 PennSeq

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2014 Feb;42(3):e20. doi: 10.1093/nar/gkt1304. Epub 2013 Dec 20.
PennSeq: accurate isoform-specific gene expression quantification in RNA-Seq by modeling non-uniform read distribution.
Hu Y1, Liu Y, Mao X, Jia C, Ferguson JF, Xue C, Reilly MP, Li H, Li M.