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The SourceForge OpenRasMol project is an adjunct to the RasMol and OpenrasMol project at http://rasmol.org. It is hoped that the SourceForge OpenRasMol project will provide a convenient focal point for active collaborative contributions.
MIRA V5 is available only on GitHub!
The V4 version released here on SourceForge stay up as some automated release fetching packages rely on V4.
MIRA - Sequence assembler and sequence mapping for whole genome shotgun and EST / RNASeq sequencing data. Can use Sanger, 454, Illumina and IonTorrent data. PacBio: CCS and error corrected data usable, uncorrected not yet.
XMIPP is an image processing suite for 3D-reconstruction of biological specimens from transmission electron microscopy data. NOTE that stable releases (including binaries) are longer stored at Sourceforge, but are available at http://xmipp.cnb.csic.es
A software package for estimating generalized ensemble weights in Mark
We have moved to GitHub:
https://github.com/muninnorg/muninn
As of July 2015 we have moved to GitHub. The SourceForge page will preserved, with the old releases.
Muninn is a software package for estimating generalized ensemble weights in Markov chain Monte Carlo (MCMC) simulations. The method is full automated and makes use of the generalized multihistogram (GMH) equations for estimation the density of states [1]. The package is implemented in C++ and has a convenient interface.
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XMIPP is an image processing suite for 3D-reconstruction of biological specimens from transmission electron microscopy data. NOTE that stable releases (including binaries) are longer stored at Sourceforge, but are available at http://xmipp.cnb.csic.es
deFuse is a software package for gene fusion discovery using RNA-Seq data.
deFuse .tar.gz bundles will be released periodically on the sourceforge site, see Files. Questions can be posted to the sourceforge discussion forum. The sourceforge wiki is depracated in favour of documentation included with the package.
Development of deFuse is on the bitbucket site, linked below.
Software for making Clusters of Orthologous Groups (featuring the new EdgeSearch algorithm). Latest ref: Kristensen DM, Kannan L, Coleman MK, Wolf YI, Sorokin A, Koonin EV, Mushegian A. Bioinformatics 2010.