GenePattern 3.9.11 – Genomic Analysis Platform

GenePattern 3.9.11

:: DESCRIPTION

GenePattern is a powerful genomic analysis platform that provides access to more than 125 tools for gene expression analysis, proteomics, SNP analysis and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.

GenePattern provides access to a broad array of computational methods used to analyze genomic data. Its extendable architecture makes it easy for computational biologists to add analysis and visualization modules, which ensures that GenePattern users have access to new computational methods on a regular basis.

::DEVELOPER

The GenePattern team

:: SCREENSHOTS

:: REQUIREMENTS

  • Java VM
  • MacOSX/Windows/Linux
  • Other Java-enabled Platforms

:: DOWNLOAD

GenePattern

:: MORE INFORMATION

Citation

ATARiS: computational quantification of gene suppression phenotypes from multisample RNAi screens.
Shao DD, Tsherniak A, Gopal S, Weir BA, Tamayo P, Stransky N, Schumacher SE, Zack TI, Beroukhim R, Garraway LA, Margolin AA, Root DE, Hahn WC, Mesirov JP.
Genome Res. 2013 Apr;23(4):665-78. doi: 10.1101/gr.143586.112.

Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov JP
GenePattern 2.0
Nature Genetics 38 no. 5 (2006): pp500-501

SEQ v0.9.4 – Language for Bioinformatics

SEQ v0.9.4

:: DESCRIPTION

SEQ is a programming language for computational genomics and bioinformatics. With a Python-compatible syntax and a host of domain-specific features and optimizations, Seq makes writing high-performance genomics software as easy as writing Python code, and achieves performance comparable to (and in many cases better than) C/C++.

::DEVELOPER

Bonnie Berger 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Python

:: DOWNLOAD

SEQ

:: MORE INFORMATION

Citation:

Ariya Shajii et al.
Seq: a high-performance language for bioinformatics
Proceedings of the ACM on Programming LanguagesOctober 2019 Article No.: 125 https://doi.org/10.1145/3360551

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.