 Version 9.1.0 home screen | |
| Operating system | UNIX, Linux, Mac, MS-Windows |
|---|---|
| Type | Bioinformatics tool |
| License | CPL 1.0 |
| Website | bioviz |
Integrated Genome Browser (IGB) (pronounced Ig-Bee) [1] is an open-source genome browser, a visualization tool used to observe biologically-interesting patterns in genomic data sets, including sequence data, gene models, alignments, and data from DNA microarrays.
Integrated Genome Browser was first developed at Affymetrix for their scientists and public sector collaborators to visualize data from genome-wide tiling arrays. The first iterations of IGB were developed using funding from NIH awarded to company scientists Gregg Helt and Tom Gingeras. In 2004, Affymetrix released IGB as open source software, along with the Genoviz SDK, a graphics library for building genome browser applications. The first release of the code base was done as a compressed file archive. Soon after, the code was imported into a new repository at SourceForge. Since then, all development has proceeded in public under an open source model. In early 2008, a group led by former Affymetrix employee Ann Loraine began developing and maintaining IGB, supported by funding from the National Science Foundation and new investigator funds from UNC Charlotte. Since then, Loraine, her students, and collaborators have added many new features and capabilities, notably support for visualizing high-throughput sequencing data from Illumina and other platforms. In 2014, they migrated the source code to a git repository at Bitbucket.
In 2020, Oracle's Java Magazine named the Integrated Genome Browser as one of the 25 greatest Java apps ever written. [2]
IGB is built on top of the Genoviz SDK, [3] a Java library that implements key visualization features such as dynamic, real-time zooming and scrolling through a genomic map, a feature of the IGB browser that sets it apart from many similar tools.
IGB is also distinguished by the ease with which individual labs can set up data source servers to share data, notably, via REST-style Web services (Distributed Annotation System) and a simple file-system based approach called QuickLoad.
IGB reads data in dozens of formats, including BAM, BED, Affymetrix CHP, FASTA, GFF, GTF, PSL, SGR, and WIG. The most up-to-date list is available at the BioViz Wiki.
IGB can output visualized data in dozens of formats via the FreeHEP library. These include EPS, PostScript, PDF, EMF, SVG, SWF, CGM, GIF, PNG, and PPM.
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In bioinformatics, sequence analysis is the process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods to understand its features, function, structure, or evolution. It can be performed on the entire genome, transcriptome or proteome of an organism, and can also involve only selected segments or regions, like tandem repeats and transposable elements. Methodologies used include sequence alignment, searches against biological databases, and others.
BioJava is an open-source software project dedicated to provide Java tools to process biological data. BioJava is a set of library functions written in the programming language Java for manipulating sequences, protein structures, file parsers, Common Object Request Broker Architecture (CORBA) interoperability, Distributed Annotation System (DAS), access to AceDB, dynamic programming, and simple statistical routines. BioJava supports a range of data, starting from DNA and protein sequences to the level of 3D protein structures. The BioJava libraries are useful for automating many daily and mundane bioinformatics tasks such as to parsing a Protein Data Bank (PDB) file, interacting with Jmol and many more. This application programming interface (API) provides various file parsers, data models and algorithms to facilitate working with the standard data formats and enables rapid application development and analysis.
BioPerl is a collection of Perl modules that facilitate the development of Perl scripts for bioinformatics applications. It has played an integral role in the Human Genome Project.
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GenePattern is a freely available computational biology open-source software package originally created and developed at the Broad Institute for the analysis of genomic data. Designed to enable researchers to develop, capture, and reproduce genomic analysis methodologies, GenePattern was first released in 2004. GenePattern is currently developed at the University of California, San Diego.
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GeneNetwork is a combined database and open-source bioinformatics data analysis software resource for systems genetics. This resource is used to study gene regulatory networks that link DNA sequence differences to corresponding differences in gene and protein expression and to variation in traits such as health and disease risk. Data sets in GeneNetwork are typically made up of large collections of genotypes and phenotypes from groups of individuals, including humans, strains of mice and rats, and organisms as diverse as Drosophila melanogaster, Arabidopsis thaliana, and barley. The inclusion of genotypes makes it practical to carry out web-based gene mapping to discover those regions of genomes that contribute to differences among individuals in mRNA, protein, and metabolite levels, as well as differences in cell function, anatomy, physiology, and behavior.
Dart is a programming language designed by Lars Bak and Kasper Lund and developed by Google. It can be used to develop web and mobile apps as well as server and desktop applications.
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CGView is a freely available downloadable Java software program, applet and API for generating colorful, zoomable, hyperlinked, richly annotated images of circular genomes such as bacterial chromosomes, mitochondrial DNA and plasmids. It is commonly used in bacterial sequence annotation pipelines to generate visual output suitable for the web. It has also been used in a variety of popular web servers and databases (BacMap).
The High-performance Integrated Virtual Environment (HIVE) is a distributed computing environment used for healthcare-IT and biological research, including analysis of Next Generation Sequencing (NGS) data, preclinical, clinical and post market data, adverse events, metagenomic data, etc. Currently it is supported and continuously developed by US Food and Drug Administration, George Washington University, and by DNA-HIVE, WHISE-Global and Embleema. HIVE currently operates fully functionally within the US FDA supporting wide variety (+60) of regulatory research and regulatory review projects as well as for supporting MDEpiNet medical device postmarket registries. Academic deployments of HIVE are used for research activities and publications in NGS analytics, cancer research, microbiome research and in educational programs for students at GWU. Commercial enterprises use HIVE for oncology, microbiology, vaccine manufacturing, gene editing, healthcare-IT, harmonization of real-world data, in preclinical research and clinical studies.
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Echinobase is a Model Organism Database (MOD). It supports the international research community by providing a centralized, integrated web based resource to access the diverse and rich, functional genomics data of echinoderm evolution, development and gene regulatory networks.