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Package suites gather software packages and installation tools for specific languages or platforms. We have some for bioinformatics software.

http://docs.bpipe.org/ - Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'. January 20th, 2016 - New! Bpipe 0.9.9 released! Download latest, all Documentation Mailing List (Google...

drive5.com - USEARCH >Extreme high-throughput sequence analysis. Orders of magnitude faster than BLAST. MUSCLE >Multiple sequence alignment. Faster and more accurate than CLUSTALW.  UPARSE >OTU clustering for 16S and other marker genes....

wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class...

The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods...

broadinstitute.github.io - Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the Hts-specs repository. See especially the SAM specification and the VCF...

github.com - Canu is a fork of the Celera Assembler designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered. Canu is...

http://www.ub.edu/dnasp/ - DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly...

Some five points to keep in mind for bioinformatics software/tools

Creators of software widely used in computational biology discuss the factors that contributed to their success