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Interactive Python based interface to Rosetta molecular modeling suite. Stand alone Python based implementation of Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using major Rosetta sampling and scoring functions.
Proper citation: PyRosetta (RRID:SCR_018541) Copy
The free Segway software package contains a novel method for analyzing multiple tracks of functional genomics data. The method uses a dynamic Bayesian network (DBN) model, which enables it to analyze the entire genome at 1-bp resolution even in the face of heterogeneous patterns of missing data. This method is the first application of DBN techniques to genome-scale data and the first genomic segmentation method designed for use with the maximum resolution data available from ChIP-seq experiments without downsampling. Segway uses the Graphical Models Toolkit (GMTK) for efficient DBN inference. The software has extensive documentation and was designed from the outset with external users in mind.
Proper citation: Segway - a way to segment the genome (RRID:SCR_004206) Copy
A collection of bioinformatics tools that can be pieced together in a very easy and flexible manner to perform both simple and complex tasks. The Biopieces work on a data stream in such a way that the data stream can be passed through several different Biopieces, each performing one specific task: modifying or adding records to the data stream, creating plots, or uploading data to databases and web services. The Biopieces are executed in a command line environment where the data stream is initialized by specific Biopieces which read data from files, databases, or web services, and output records to the data stream that is passed to downstream Biopieces until the data stream is terminated at the end of the analysis. The advantage of the Biopieces is that a user can easily solve simple and complex tasks without having any programming experience. Moreover, since the data format used to pass data between Biopieces is text based, different developers can quickly create new Biopieces in their favorite programming language - and all the Biopieces will maintain compatibility. Finally, templates exist for creating new Biopieces in Perl and Ruby. There are currently ~190 Biopieces (March 2014).
Proper citation: Biopieces (RRID:SCR_005783) Copy
http://www.biochem.ucl.ac.uk/bsm/virus_database/VIDA3/VIDA.html
VIDA contains a collection of homologous protein families derived from open reading frames from complete and partial virus genomes. For each family, users can get an alignment of the conserved regions, functional and taxonomy information, and links to DNA sequences and structures. * Search homologous protein families from particular virus families * Links to complete genome sequence: Arteriviridae, Coronaviridae, Herpesviridae, Poxviridae The Virus Database at University College London has been developed as a system to organize animal virus open reading frame sequences. All known and predicted protein sequences from complete and partial genomes of particular virus families are extracted from GenBank and filtered to remove 100% redundancy. On the basis of sequence similarity the sequences are then clustered into homologous protein families (HPFs). The families are enriched with annotations including function and functional classification, related protein structures, taxonomy, length of the proteins, boundaries of the conserved region/s, virus-specific gene name and links to EMBL entries and SWISSPROT., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: VIDA (RRID:SCR_007111) Copy
http://cudasw.sourceforge.net/
CUDASW++ is a bioinformatics software for Smith-Waterman protein database searches that takes advantage of the massively parallel CUDA architecture of NVIDIA Tesla GPUs to perform sequence searches 10x-50x faster than NCBI BLAST. In this algorithm, we deeply explore the SIMT (Single Instruction, Multiple Thread) and virtualized SIMD (Single Instruction, Multiple Data) abstractions to achieve fast speed. This algorithm has been fully tested on Tesla C1060, Tesla C2050, GeForce GTX 280 and GTX 295 graphics cards, and has been incorporated to NVIDIA Tesla Bio Workbench. * Operating System: Linux * Programming language: CUDA and C * Other requirements: CUDA SDK and Toolkits 2.0 or higher
Proper citation: CUDASW++ (RRID:SCR_008862) Copy
http://bioen-compbio.bioen.illinois.edu/FusionHunter/
Software for identifying fusion transcripts using paired-end RNA-seq.
Proper citation: FusionHunter (RRID:SCR_011895) Copy
https://gitlab.com/kyrgyzov/lsa_slurm
Software tool to implement pre-assembly binning scheme leveraging sparse dictionary learning and matrix factorization to solve sparse decomposition problems arising in field of metagenomics.
Proper citation: lsa_slurm (RRID:SCR_018134) Copy
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