Hi-Jack – Pathway-based Inference of Host-pathogen Interactions

Hi-Jack

:: DESCRIPTION

Hi-Jack, a novel computational framework, for inferring pathway-based interactions between a host and a pathogen that relies on the idea of metabolite hijacking.

::DEVELOPER

InfoCloud Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / MacOsX / Linux
  • C++ Compiler

:: DOWNLOAD

Hi-Jack

:: MORE INFORMATION

Citation:

Hi-Jack: A novel computational framework for pathway-based inference of host-pathogen interactions.
Kleftogiannis D, Wong L, Archer JA, Kalnis P.
Bioinformatics. 2015 Mar 9. pii: btv138

TopoGSA – Network Topological Gene Set Analysis

TopoGSA

:: DESCRIPTION

TopoGSA (Topology-based Gene Set Analysis) computes and visualise the topological properties of a set of genes/proteins mapped onto a molecular interaction network. Different topological characteristics, such as the centrality of nodes in the network or their tendency to form clusters, are computed and compared against those of known cellular pathways and processes (KEGG, BioCarta, GO, etc.).

::DEVELOPER

TopoGSA team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Bioinformatics. 2010 May 1;26(9):1271-2. doi: 10.1093/bioinformatics/btq131. Epub 2010 Mar 24.
TopoGSA: network topological gene set analysis.
Glaab E, Baudot A, Krasnogor N, Valencia A.

PathExpand – Extending Cellular Pathways in Interaction Networks

PathExpand

:: DESCRIPTION

PathExpand is a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and expanding them to include densely interconnected interaction partners.

::DEVELOPER

PathExpand team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

E. Glaab, A. Baudot, N. Krasnogor, A. Valencia
Extending pathways and processes using molecular interaction networks to analyse cancer genome data
in BMC Bioinformatics, 11(1):597, 2010

SIREN 1.0 – Signing of Regulatory Networks

SIREN 1.0

:: DESCRIPTION

The SIREN algorithm can infer the regulatory type (positive or negative regulation) of interactions in a known gene regulatory network given corresponding genome-wide gene expression data.

::DEVELOPER

Bader Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 WordCloud

:: MORE INFORMATION

Citation

Algorithms Mol Biol. 2015 Jul 8;10:23. doi: 10.1186/s13015-015-0054-4. eCollection 2015.
Inferring interaction type in gene regulatory networks using co-expression data.
Khosravi P#, Gazestani VH#, Pirhaji L, Law B, Sadeghi M, Goliaei B, Bader GD.

CN – Inferring Gene Regulatory Networks using SORDER algorithm

CN

:: DESCRIPTION

CN (Consensus Network) is a network inference method based on the SORDER algorithm and a suitable interval threshold for Conditional Mutual Information (CMI) tests

::DEVELOPER

School of Biological Sciences, Iran

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOsX
  • MatLab

:: DOWNLOAD

 CN

:: MORE INFORMATION

Citation

CN: a consensus algorithm for inferring gene regulatory networks using the SORDER algorithm and conditional mutual information test.
Aghdam R, Ganjali M, Zhang X, Eslahchi C.
Mol Biosyst. 2015 Mar;11(3):942-9. doi: 10.1039/c4mb00413b

IPCA-CMI – Inferring Gene Regulatory Networks based on Combination of PCA-CMI and MIT score

IPCA-CMI

:: DESCRIPTION

IPCA-CMI is an algorithm for inferring gene regulatory networks based on a combination of PCA-CMI and MIT score.

::DEVELOPER

School of Biological Sciences, Iran

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOsX
  • MatLab

:: DOWNLOAD

 IPCA-CMI

:: MORE INFORMATION

Citation

PLoS One. 2014 Apr 11;9(4):e92600. doi: 10.1371/journal.pone.0092600. eCollection 2014.
IPCA-CMI: an algorithm for inferring gene regulatory networks based on a combination of PCA-CMI and MIT score.
Aghdam R1, Ganjali M1, Eslahchi C

CyClus3D 3.3 – Cytoscape plugin for Identifying Functional Modules

CyClus3D 3.3

:: DESCRIPTION

CyClus3D is a Cytoscape plugin for identifying functional modules in integrated networks composed of multiple interaction types. CyClus3D operates by clustering user-defined 3-node network motifs.

::DEVELOPER

Van de Peer Lab

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 CyClus3D

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Jun 1;27(11):1587-8. doi: 10.1093/bioinformatics/btr182.
CyClus3D: a Cytoscape plugin for clustering network motifs in integrated networks.
Audenaert P1, Van Parys T, Brondel F, Pickavet M, Demeester P, Van de Peer Y, Michoel T.

CoExpNetViz 1.0.4 – Comparative Co-Expression Network Construction and Visualization

CoExpNetViz 1.0.4

:: DESCRIPTION

CoExpNetViz takes as input a set of bait genes chosen by you and at least one pre-processed gene expression dataset. You can also specify a negative and positive cutoff value, which will be used to determine if two genes are co-expressed or not.

::DEVELOPER

Van de Peer Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux
  • Java
  • Cytoscape

:: DOWNLOAD

CoExpNetViz

:: MORE INFORMATION

Citation

CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool.
Tzfadia O, Diels T, De Meyer S, Vandepoele K, Aharoni A, Van de Peer Y.
Front Plant Sci. 2016 Jan 5;6:1194. doi: 10.3389/fpls.2015.01194

lemon-tree 3.0.4 – Biological Module Network Inference

lemon-tree 3.0.4

:: 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

lemon-tree team

:: 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.

Diffany 1.0.0 – Calculating and Visualizing Differential Molecular Networks

Diffany 1.0.0

:: DESCRIPTION

Diffany is an open-source toolbox for calculating and visualizing differential networks. It is packaged in three separate modules: the algorithms as the core library, a commandline interface to generate Diffany networks through the console, and a cytoscape plugin for generation, visualisation and easy manipulation of the input and output networks.

::DEVELOPER

Van de Peer Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Java
  • CytoScape

:: DOWNLOAD

 Diffany

:: MORE INFORMATION

Citation

Diffany: an ontology-driven framework to infer, visualise and analyse differential molecular networks.
Van Landeghem S, Van Parys T, Dubois M, Inzé D, Van de Peer Y.
BMC Bioinformatics. 2016 Jan 5;17:18. doi: 10.1186/s12859-015-0863-y.