lemon-tree 3.0.3 – Biological Module Network Inference

lemon-tree 3.0.3

:: DESCRIPTION

LemonTree (former LeMoNe) is an algorithm to infer a module network from biological data. It can integrate heterogeneous data types such as expression data, copy number, microRNA, epigenetic profiles.

::DEVELOPER

Tom Michoel

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/windows/MacOsX
  • Java

:: DOWNLOAD

 lemon-tree

:: MORE INFORMATION

Citation:

Integrative multi-omics module network inference with Lemon-Tree.
Bonnet E, Calzone L, Michoel T.
PLoS Comput Biol. 2015 Feb 13;11(2):e1003983. doi: 10.1371/journal.pcbi.1003983.

Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development.
Vermeirssen V, Joshi A, Michoel T, Bonnet E, Casneuf T, Van de Peer Y.
Mol Biosyst. 2009 Dec;5(12):1817-30. Epub 2009 Jul 17.

SurvBART – R Package for Bayesian Ensemble Methods for Survival Prediction in gene expression data

SurvBART

:: DESCRIPTION

SurvBART is the R package for the methods described in Bayesian ensemble methods for survival prediction in gene expression data

::DEVELOPER

Veera Baladandayuthapani.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R Package

:: DOWNLOAD

 SurvBART

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Feb 1;27(3):359-67. doi: 10.1093/bioinformatics/btq660. Epub 2010 Dec 8.
Bayesian ensemble methods for survival prediction in gene expression data.
Bonato V, Baladandayuthapani V, Broom BM, Sulman EP, Aldape KD, Do KA.

ArrayCluster 1.0 – Mixed Factors Analysis of Microarray Gene Expression Data

ArrayCluster 1.0

:: DESCRIPTION

ArrayCluster is one of the significant challenges in gene expression analysis to find unknown subtypes of several diseases at the molecular levels. This task can be addressed by grouping gene expression patterns of the collected samples on the basis of a large number of genes. Application of commonly used clustering methods to such a dataset however are likely to fail due to over-learning, because the number of samples to be grouped is much smaller than the data dimension which is equal to the number of genes involved in the dataset. To overcome such difficulty, we developed a novel model-based clustering method, referred to as the mixed factors analysis.

::DEVELOPER

ArrayCluster Team

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 ArrayCluster

:: MORE INFORMATION

Citation

Bioinformatics. 2006 Jun 15;22(12):1538-9.
ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles.
Yoshida R, Higuchi T, Imoto S, Miyano S.

Excavator 2.0 – Gene Expression Data Clustering

Excavator 2.0

:: DESCRIPTION

Excavator (EXpression data Clustering Analysis and VisualizATiOn Resource) is a computer software program for gene expression data clustering. It uses a set of unique clustering algorithms developed by the Computational Systems Biology Lab (CSBL) at the University of Georgia. Excavator represents data internally as a minimum spanning tree and outputs results to the user through the use of a micro-array data window, graphs, and a dendrogram viewer.

::DEVELOPER

The Computational Systems Biology Lab

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Java

:: DOWNLOAD

 Excavator

:: MORE INFORMATION

Citation

Dong Xu, Victor Olman, Li Wang and Ying Xu
Excavator: a computer program for efficiently mining gene expression data
Nucl. Acids Res. (2003) 31 (19): 5582-5589.

DLMM 0.0.2 – Double-layered Mixture Model for Joint Analysis of Copy Number and Gene Expression Data

DLMM 0.0.2

:: DESCRIPTION

DLMM (Double-layered Mixture Model) is a software to select copy number-associated gene expression changes in high-throughput genomics data. Copy number segmentation results and criterion-based gene selection are separately reported.

::DEVELOPER

Hyungwon Choi

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • C Compiler

:: DOWNLOAD

  DLMM

:: MORE INFORMATION

Citation:

H. Choi, Z.S. Qin, and D. Ghosh (2010),
A Double-layered Mixture Model for Joint Analysis of Copy Number and Gene Expression Data.
J. Comput. Biol. 17(2):1-17.

topGO 0.97 – Calculat Significance of Biological Terms from Gene Expression Data

topGO 0.97

:: DESCRIPTION

topGO (topology-based Gene Ontology scoring) is a software package for calculating the significance of biological terms from gene expression data. It implements various standard and advanced new algorithms for determining the relevance of Gene Ontology groups from microarrays. A specific feature of the advanced algorithms is the exploitation of the hierarchical graph structure of the GO annotation for coping with the large number of GO groups. Often, related biological terms are scored with a similar statistical significance. Dependencies between GO terms can be de-correlated by accounting for the neighborhood of a GO node when calculating its significance. The new algorithms better detect significant GO terms from gene expression data.

::DEVELOPER

Adrian Alexa  , Max-Planck-Institut Informatik

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 topGO

:: MORE INFORMATION

Citation:

Alexa, A.; Rahnenführer, J.; Lengauer, T.,
Improved scoring of functional groups from gene expression data by decorrelating GO graph structure.
Bioinformatics 2006, 22 (13), 1600-7.

Caryoscope 0.4.0 – View Gene Expression Data in Genome

Caryoscope 0.4.0

:: DESCRIPTION

Caryoscope is  an application  for viewing gene expression data in a whole-genome context. Caryoscope has been used to “draw” microarray data onto a set of chromosomes so that changes in DNA copy number can identify regions of chromosome loss or duplication within the genome of tumor cells (Nat Genet. 1999 Sep;23(1):41-6). In addition, microarray data measuring mRNA expression levels can also be visualized in a genomic context using Caryoscope (PNAS 2002 Dec 10;99(25):16144-9). Data viewed with Caryscope need not be limited to microarray data — any type of numerical data that can be represented as a function of genomic position can be visualized using Caryoscope.

::DEVELOPER

Ihab A.B. Awad, Gavin Sherlock etc.

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / Max OS X
  • JAVA

:: DOWNLOAD

Caryoscope

:: MORE INFORMATION

Citation:

.Awad, I.A.B, Rees, C.A., Hernandez-Boussard, T., Ball, C.A. and Sherlock, G. (2004)
Caryoscope: An Open Source Java Application for Viewing Microarray Data in a Genomic Context.
BMC Bioinformatics 5:151.

ORIOGEN 4.01 – Analyzes Gene Expression data obtained from Time-course/Dose-response studies

ORIOGEN 4.01

:: DESCRIPTION

ORIOGEN (Order Restricted Inference for Ordered Gene Expression) analyzes gene expression data obtained from time-course/dose-response studies.

::DEVELOPER

ShareShyamal D. Peddada, Ph.D.

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows /MacOsX
  • Java 

:: DOWNLOAD

 ORIOGEN

:: MORE INFORMATION

Citation:

Bioinformation. 2007 Apr 10;1(10):414-9.
Order-restricted inference for ordered gene expression (ORIOGEN) data under heteroscedastic variances.
Simmons SJ, Peddada SD.

Trixy – Cluster of various types of Gene Expression data

Trixy

:: DESCRIPTION

Trixy is used for clustering of various types of data, mostly designed for gene expression data.Trixy constructs a graph and computes the local density around each node (called curvature).It then extracts clusters of high density.

::DEVELOPER

The TAGC Laboratory

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux  / WIndows / MacOsX
  • C Compiler

:: DOWNLOAD

  Trixy

:: MORE INFORMATION

Citation:

J. Rougemont and P. Hingamp :
DNA Microarray Data and Contextual Analysis of Correlation Graphs
BMC Bioinformatics 2003 4 :15.

Dancer 1.1.1 – Digital Anatomical Reconstruction of Gene Expression data

Dancer 1.1.1

:: DESCRIPTION

DANCER (Digital Anatomy Constructor) is a program that can be used to reconstruct anatomical pictures. In general, it fills color into drawn shapes that collectively form a picture that represents the data. The main data source of this program is microarray data, but in situ hybridization-, Northern Blot-, Southern Blot- or any other data can be used. As a result, a picture (for example, a brain section from mouse) is produced where the shapes (for example, brain regions like the hypothalamus) are filled with color that corresponds to the gene expression level.

::DEVELOPER

Liisa Holm’s Bioinformatics Group

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

  DANCER

:: MORE INFORMATION

 

Citation:

Kankainen M and Wong G. (2003)
DANCER: a program for digital anatomical reconstruction of gene expression data.
Nucleic Acids Res, 31, e132.