BioJS 2.0 – A library of JavaScript Components to Represent Biological Data

BioJS 2.0

:: DESCRIPTION

BioJS is an open-source project whose main objective is the visualization of biological data in JavaScript. BioJS provides an easy-to-use consistent framework for bioinformatics application programmers.

::DEVELOPER

BioJS team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows / MacOsX
Java

:: DOWNLOAD

BioJS

:: MORE INFORMATION

Citation

BioJS: an open source JavaScript framework for biological data visualization.
Gómez J, García LJ, Salazar GA, Villaveces J, Gore S, García A, Martín MJ, Launay G, Alcántara R, Del-Toro N, Dumousseau M, Orchard S, Velankar S, Hermjakob H, Zong C, Ping P, Corpas M, Jiménez RC.
Bioinformatics. 2013 Apr 15;29(8):1103-4.

Encore 1.1 – GWAS and Biological Data Analysis tool

Encore 1.1

:: DESCRIPTION

Encore is a free, open-source command-line tool for analysis of GWAS (SNP) and other types of biological data.

::DEVELOPER

Insilico Research Group (McKinney Laboratory for Bioinformatics and In Silico Modeling)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

Encore

:: MORE INFORMATION

Citation

Genet Epidemiol. 2013 Sep;37(6):614-21. doi: 10.1002/gepi.21739. Epub 2013 Jun 5.
Encore: Genetic Association Interaction Network centrality pipeline and application to SLE exome data.
Davis NA1, Lareau CA, White BC, Pandey A, Wiley G, Montgomery CG, Gaffney PM, McKinney BA.

Scriptome – Protocols for Manipulating Biological Data

Scriptome

:: DESCRIPTION

The Scriptome is a set of tools that filter, format, and merge data in tabular or common biological formats. Use single tools to take a quick look at data, or string tools together in a protocol to explore the data more deeply.

::DEVELOPER

Computational Biology Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / MacOsX / Linux
Perl

:: DOWNLOAD

Scriptome

:: MORE INFORMATION

MetaOmGraph 1.8.1 – Plotting and Analyzing large sets of Biological data

MetaOmGraph 1.8.1

:: DESCRIPTION

MetaOmGraph is a tool for plotting and analyzing large sets of data while using as little memory as possible. It was designed with biological experiment data in mind.

::DEVELOPER

Wurtele Lab

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows / MacOsX
Java

:: DOWNLOAD

MetaOmGraph

:: MORE INFORMATION

Citation:

Chem Biodivers. 2012 May;9(5):868-87. doi: 10.1002/cbdv.201100355.
Massive human co-expression network and its medical applications.
Feng Y, Hurst J, Almeida-De-Macedo M, Chen X, Li L, Ransom N, Wurtele ES.

PathRings 1.0 – A web-version of Biological Data Visualization Framework

PathRings 1.0

:: DESCRIPTION

PathRings is a new interactive web-based, scalable biological pathway visualization tool for biologists to explore and interpret biological pathways.

::DEVELOPER

PathRings team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web browser

:: DOWNLOAD

PathRings

:: MORE INFORMATION

Citation

PathRings: a web-based tool for exploration of ortholog and expression data in biological pathways.
Zhu Y, Sun L, Garbarino A, Schmidt C, Fang J, Chen J.
BMC Bioinformatics. 2015 May 19;16:165. doi: 10.1186/s12859-015-0585-1.

InterMine 5.0.3 – Open Source Biological Data Warehouse System

InterMine 5.0.3

:: DESCRIPTION

InterMine is an open source data warehouse built specifically for the integration and analysis of complex biological data.InterMine enables the creation of biological databases accessed by sophisticated web query tools.

::DEVELOPER

the Micklem lab at the University of Cambridge

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Web Server
Java
PostgreSQL
TomCat
Perl

:: DOWNLOAD

InterMine

:: MORE INFORMATION

Citation

InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data.
Smith RN, Aleksic J, Butano D, Carr A, Contrino S, Hu F, Lyne M, Lyne R, Kalderimis A, Rutherford K, Stepan R, Sullivan J, Wakeling M, Watkins X, Micklem G.
Bioinformatics. 2012 Dec 1;28(23):3163-5. doi: 10.1093/bioinformatics/bts577.

Ontologizer 2.1 – Analysis and Visualization of High-Throughput Biological Data Using Gene Ontology

Ontologizer 2.1

:: DESCRIPTION

Ontologizer is a Java webstart application for GO term enrichment analysis that provides browsing and graph visualization capabilities. The Ontologizer allows users to analyze data with the standard Fisher exact test and also the parent-child method and topology methods.

::DEVELOPER

The Computational Biology @ Charité Berlin

:: SCREENSHOTS

:: REQUIREMENTS

Linux / MacOsX / Windows
Java

:: DOWNLOAD

Ontologizer

:: MORE INFORMATION

Citation

Bioinformatics. 2008 Jul 15;24(14):1650-1. Epub 2008 May 29.
Ontologizer 2.0–a multifunctional tool for GO term enrichment analysis and data exploration.
Bauer S, Grossmann S, Vingron M, Robinson PN.

Fizzy v1.4 – Feature Selection for Biological Data Formats

Fizzy v1.4

:: DESCRIPTION

Fizzy is a feature subset selection tool that uses FEAST in the background to run feature selection on biological data formats.

::DEVELOPER

Drexel’s EESI Lab.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/ Linux /MacOsX
Python

:: DOWNLOAD

Fizzy

:: MORE INFORMATION

Citation

Fizzy: feature subset selection for metagenomics.
Ditzler G, Morrison JC, Lan Y, Rosen GL.
BMC Bioinformatics. 2015 Nov 4;16:358. doi: 10.1186/s12859-015-0793-8.

BioJava 5.4.0 – Java Framework for Processing Biological Data

BioJava 5.4.0

:: DESCRIPTION

BioJava is a mature open-source project that provides a framework for processing of biological data. BioJava contains powerful analysis and statistical routines, tools for parsing common file formats and packages for manipulating sequences and 3D structures. It enables rapid bioinformatics application development in the Java programming language.

::DEVELOPER

BioJava Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows / Mac OsX
Java
Maven

:: DOWNLOAD

BioJava

:: MORE INFORMATION

Citation:

BioJava: an open-source framework for bioinformatics in 2012.
Prlić A, Yates A, Bliven SE, Rose PW, Jacobsen J, Troshin PV, Chapman M, Gao J, Koh CH, Foisy S, Holland R, Rimsa G, Heuer ML, Brandstätter-Müller H, Bourne PE, Willis S.
Bioinformatics. 2012 Oct 15;28(20):2693-5. doi: 10.1093/bioinformatics/bts494.

BioJava: an Open-Source Framework for Bioinformatics ,
Holland RC, Down TA, Pocock M, Prlić A, Huen D, James K, Foisy S, Dräger A, Yates A, Heuer M, Schreiber MJ.
Bioinformatics. 2008 Sep 15;24(18):2096-7. doi: 10.1093/bioinformatics/btn397.

MOBY 1.16 / BioMoby – Interoperability between Biological Data Hosts and Analytical Services

MOBY 1.16 / BioMoby

:: DESCRIPTION

MOBY (Model Organism Bring Your) system defines an ontology-based messaging standard through which a client will be able to automatically discover and interact with task-appropriate biological data and analytical service providers, without requiring manual manipulation of data formats as data flows from one provider to the next. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach.

::DEVELOPER

The BioMoby Consortium

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows / Mac OsX
Perl

:: DOWNLOAD

MOBY

:: MORE INFORMATION

Citation

The BioMoby Consortium (2008)
Interoperability with Moby 1.0 — It’s better than sharing your toothbrush!
Briefings in Bioinformatics, 9 (3), pp. 220-231.