Cytoscape 3.7.2 – Platform for Complex-Network Analysis & Visualization

Cytoscape 3.7.2

:: DESCRIPTION

Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization.

::DEVELOPER

Cytoscape Team

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

Cytoscape

:: MORE INFORMATION

Citation:

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T.
Cytoscape: a software environment for integrated models of biomolecular interaction networks.
Genome Research 2003 Nov; 13(11):2498-504

canEvolve – Integrative Cancer Genomics analysis of Expression, Copy Number, miRNAs and Network

canEvolve

:: DESCRIPTION

canEvolve query functionalities are designed to fulfill most frequent analysis needs of cancer researchers with a view to generate novel hypotheses. canEvolve stores gene, microRNA (miRNA) and protein expression profiles, copy number alterations for multiple cancer types, and protein-protein interaction information. canEvolve allows querying of results of primary analysis, integrative analysis and network analysis of oncogenomics data. The querying for primary analysis includes differential gene and miRNA expression as well as changes in gene copy number measured with SNP microarrays. At present canEvolve provides different types of information extracted from 90 cancer genomics studies comprising of more than 10,000 patients. The presence of multiple data types, novel integrative analysis for identifying regulators of oncogenesis, network analysis and ability to query gene lists/pathways are distinctive features of canEvolve. canEvolve will facilitate integrative and meta-analysis of oncogenomics datasets.

::DEVELOPER

CanEvolve Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

canEvolve: a web portal for integrative oncogenomics.
Samur MK, Yan Z, Wang X, Cao Q, Munshi NC, Li C, Shah PK.
PLoS One. 2013;8(2):e56228. doi: 10.1371/journal.pone.0056228.

KNOWENG – Knowledge Engine for Genomics

KNOWENG

:: DESCRIPTION

KnowEnG enables knowledge-guided machine learning and graph mining analysis on genomic datasets using scalable cloud computation and exploration of results with interactive visualizations.

::DEVELOPER

The Sinha Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

NO

:: MORE INFORMATION

Citation:

KnowEnG: a knowledge engine for genomics.
Sinha S, Song J, Weinshilboum R, Jongeneel V, Han J.
J Am Med Inform Assoc. 2015 Nov;22(6):1115-9. doi: 10.1093/jamia/ocv090.

BioPig 2.0 – Hadoop-based analytic toolkit for large-scale Sequence data

BioPig 2.0

:: DESCRIPTION

BioPig is a framework for genomic data analysis using Apache Pig and Hadoop.

::DEVELOPER

Zhong Wang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /  MacOsX
  • Apache’s Hadoop MapReduce system
  • Pig data flow language

:: DOWNLOAD

 BioPig

:: MORE INFORMATION

Citation

BioPig: a Hadoop-based analytic toolkit for large-scale sequence data.
Nordberg H, Bhatia K, Wang K, Wang Z.
Bioinformatics. 2013 Dec 1;29(23):3014-9. doi: 10.1093/bioinformatics/btt528.

PROMO 2019.5.1 – Analyzing large Multi-omic datasets

PROMO 2019.5.1

:: DESCRIPTION

PROMO (Profiler of Multi-Omics data) is an interactive Matlab-based tool, designed to analyze large versatile datasets.It enables importing multi-label datasets from various file formats, data exploration and visualization, applying unsupervised analysis on both samples and features and utilizing various popular statistical tests including survival analysis. Special features that are specific to multi-omic datasets include dataset integration and joint multi-omic clustering.

::DEVELOPER

Ron Shamir’s lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/ MacOsX
  • MatLab

:: DOWNLOAD

PROMO

:: MORE INFORMATION

LiSSI 1.0 – Integrated Bioinformatics Platform for Genomic Island Analysis

LiSSI 1.0

:: DESCRIPTION

LiSSI (Life-Style-Specific-Islands) is a java tool for predicting life-style-specific genomic islands through evolutionary conservation. It is divided into three sequentially executed modules: evolutionary sequence analysis, island detection, and machine learning.

::DEVELOPER

Baumbach lab

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

LiSSI

:: MORE INFORMATION

Citation

J Integr Bioinform. 2017 Jul 5;14(2). pii: /j/jib.2017.14.issue-2/jib-2017-0010/jib-2017-0010.xml. doi: 10.1515/jib-2017-0010.
LifeStyle-Specific-Islands (LiSSI): Integrated Bioinformatics Platform for Genomic Island Analysis.
Barbosa E, Röttger R, Hauschild AC, de Castro Soares S, Böcker S, Azevedo V, Baumbach J.

JABAWS 2.2 – JAva Bioinformatics Analysis Web Services

JABAWS 2.2

:: DESCRIPTION

JABAWS is a collection of web services for bioinformatics, and currently provides services that make it easy to access well-known multiple sequence alignment and protein disorder prediction programs from Jalview. JABAWS is free software which provides web services conveniently packaged to run on your local computer, server, cluster or Amazon EC2 instance. Services for multiple sequence alignment include Clustal Omega, Clustal W, MAFFT, MUSCLE, TCOFFEE and PROBCONS. Analysis services allow prediction of protein disorder with DisEMBL, IUPred, Ronn and GlobPlot; and calculation of amino acid alignment conservation with AACon.

::DEVELOPER

The Barton Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX/ Amazon EC2
  • Java

:: DOWNLOAD

 JABAWS

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Jul 15;27(14):2001-2. doi: 10.1093/bioinformatics/btr304. Epub 2011 May 18.
Java bioinformatics analysis web services for multiple sequence alignment–JABAWS:MSA.
Troshin PV, Procter JB, Barton GJ.

Galaxy 19.09 – Evolutionary and Data Processing Module Development

Galaxy 19.09

:: DESCRIPTION

Galaxy is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses.

::DEVELOPER

Galaxy Team

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows /  Mac OsX / Linux
  • Python

:: DOWNLOAD

 Galaxy

:: MORE INFORMATION

Citation

Genome Res. 2009 Nov;19(11):2144-53. Epub 2009 Oct 9.
Windshield splatter analysis with the Galaxy metagenomic pipeline.
Kosakovsky Pond S, Wadhawan S, Chiaromonte F, Ananda G, Chung WY, Taylor J, Nekrutenko A; Galaxy Team.

NYoSh Analysis Workbench 2.0 – Biological data analysis based on Meta Programming System

NYoSh Analysis Workbench 2.0

:: DESCRIPTION

NYoSh (Not your ordinary Shell) Analysis Workbench is a data analysis workbench built on top of MPS. Takes advantage of composable languages to create a platform intermediate between command line flexibility and user-friendly custom interfaces.

::DEVELOPER

Campagne Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R
  • Active MQ

:: DOWNLOAD

NYoSh Analysis Workbench

:: MORE INFORMATION

Citation

PeerJ. 2014 Jan 2;2:e241. doi: 10.7717/peerj.241. eCollection 2014.
Composable languages for bioinformatics: the NYoSh experiment.
Simi M, Campagne F.

MetaR 2.0.2 – Data Analysis with the R Ecosystem

MetaR 2.0.2

:: DESCRIPTION

MetaR (Metaprogramming in R) takes advantage of Language Workbench Technology to facilitate data analysis with the R language.

::DEVELOPER

Campagne Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R

:: DOWNLOAD

MetaR

:: MORE INFORMATION

Citation

Fabien Campagne, William ER Digan, Manuele Simi
MetaR: simple, high-level languages for data analysis with the R ecosystem
bioRxiv 2015 doi: http://dx.doi.org/10.1101/030254