ScalaBLAST 2.4.53 – Multiprocessor Implementation of the NCBI BLAST library

ScalaBLAST 2.4.53

:: DESCRIPTION

ScalaBLAST is a high-performance multiprocessor implementation of the NCBI BLAST library. ScalaBLAST supports all 5 primary program types (blastn, blastp, tblastn, tblastx, and blastx) and several output formats (pairwise, tabular, or XML).

:: DEVELOPER

Computational Biology & Bioinformatics ,Pacific Northwest National Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • gcc
  • MPI

:: DOWNLOAD

 ScalaBLAST

:: MORE INFORMATION

Citation

Oehmen, C.S. and J. Nieplocha. 2006.
ScalaBLAST: A scalable implementation of BLAST for high-performance data-intensive bioinformatics analysis“,
IEEE Transactions on Parallel and Distributed Systems, 17(8): 740-749.

Bioinformatics. 2013 Mar 15;29(6):797-8. doi: 10.1093/bioinformatics/btt013. Epub 2013 Jan 29.
ScalaBLAST 2.0: rapid and robust BLAST calculations on multiprocessor systems.
Oehmen CS, Baxter DJ.

SAIGE 0.44.6.5 – Scalable and Accurate Implementation of GEneralized mixed model

SAIGE 0.44.6.5

:: DESCRIPTION

SAIGE is an R-package for testing for associations between genetic variants and binary phenotypes with adjusting for sample relatedness and case-control imbalance.

::DEVELOPER

Lee lab for Statistical Genetics and Data Science

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

SAIGE

:: MORE INFORMATION

Citation

Zhou W, Nielsen JB, Fritsche LG, Dey R, Gabrielsen ME, Wolford BN, LeFaive J, VandeHaar P, Gagliano SA, Gifford A, Bastarache LA, Wei WQ, Denny JC, Lin M, Hveem K, Kang HM, Abecasis GR, Willer CJ, Lee S.
Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies.
Nat Genet. 2018 Sep;50(9):1335-1341. doi: 10.1038/s41588-018-0184-y. Epub 2018 Aug 13. PMID: 30104761; PMCID: PMC6119127.

PBWT – Implementation of Positional Burrows-Wheeler Transform for Genetic data

PBWT

:: DESCRIPTION

The pbwt package provides a core implementation and development environment for PBWT (Positional Burrows-Wheeler Transform) methods for storing and computing on genome variation data sets.

::DEVELOPER

Richard Durbin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 pbwt

:: MORE INFORMATION

Citation

Bioinformatics. 2014 May 1;30(9):1266-72. doi: 10.1093/bioinformatics/btu014. Epub 2014 Jan 9.
Efficient haplotype matching and storage using the positional Burrows-Wheeler transform (PBWT).
Durbin R.

SBMLsimulator 1.2.1 – Java Solver Implementation for SBML

SBMLsimulator 1.2.1

:: DESCRIPTION

SBMLsimulator is a fast, accurate, and easily usable program for dynamic model simulation and heuristic parameter optimization of models encoded in the Systems Biology Markup Language (SBML). In order to ensure a high reliability of this software, it has been benchmarked against the entire SBML Test Suite and all models from the Biomodels.net database. It includes a large collection of nature-inspired heuristic optimization procedures for efficient model calibration.

::DEVELOPER

the Center for Bioinformatics Tübingen (Zentrum für Bioinformatik Tübingen, ZBIT).

:: SCREENSHOTS

SBMLsimulator

:: REQUIREMENTS

  • Linux/ WIndows/MacOsX
  • Java

:: DOWNLOAD

  SBMLsimulator

:: MORE INFORMATION

Citation

Roland Keller, Alexander Dörr, Akito Tabira, Akira Funahashi, Michael J. Ziller, Richard Adams, Nicolas Rodriguez, Nicolas Le Novère, Noriko Hiroi, Hannes Planatscher, Andreas Zell, and Andreas Dräger.
The systems biology simulation core algorithm.
BMC Systems Biology, 7:55, July 2013

ReAlignerV 8.1.4 – Genomic Alignment Tool & Implementation

ReAlignerV 8.1.4

:: DESCRIPTION

ReAlignerV is an alignment tool focusing on genomic nucleotide sequences upstream of genes.

::DEVELOPER

Hisakazu IWAMA

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Perl

:: DOWNLOAD

 ReAlignerV

:: MORE INFORMATION

Citation:

Iwama H. et al.
ReAlignerV: Web-based genomic alignment tool with high specificity and robustness estimated by species-specific insertion sequences
BMC Bioinformatics. 9(1):112,

Iwama H & Gojobori T,
Highly conserved upstream sequences for transcription factor genes and implications for the regulatory network.
PNAS 2004, 101(49):17156-17161.

SynBioWave 2.0 – Google Wave Implementation for Molecular Biologists

SynBioWave 2.0

:: DESCRIPTION

SynBioWave is a Google Wave Implementation for molecular biologists. It aims to unite the stunning possibilities regarding a cooperative workflow of a web application with the comprehensive assortment of sequence tools a desktop application offers.

::DEVELOPER

SynBioWave team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac OsX / WIndows
  • JRE

:: DOWNLOAD

 SynBioWave

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Nov 1;26(21):2782-3. doi: 10.1093/bioinformatics/btq518. Epub 2010 Sep 13.
SynBioWave–a real-time communication platform for molecular and synthetic biology.
Staab PR1, Walossek J, Nellessen D, Grünberg R, Arndt KM, Müller KM.

JAWAMix5 r2 – HDF5 based JAva implementation of Whole Genome Association Studies using Mixed models

JAWAMix5 r2

:: DESCRIPTION

JAWAMix5 is an out-of-core open-source toolkit for association mapping using high-throughput sequence data. Taking advantage of its HDF5-based implementation, JAWAMix5 stores genotype data on disk and accesses them as though stored in main memory. Therefore, it offers a scalable and fast analysis without concerns about memory usage, whatever the size of the dataset. We have implemented eight functions for association studies, including standard methods (linear models, mixed linear models, rare variants test, nested association mapping (NAM), and local variance component analysis), as well as a novel Bayesian local variance component analysis. Application to real data reveals new biological insights and demonstrates that JAWAMix5 is reasonably fast compared to traditional solutions that load the complete dataset into memory, and that the memory usage is efficient regardless of the dataset size.

::DEVELOPER

Quan Long

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows / MacOsX
  • Java

:: DOWNLOAD

 JAWAMix5

:: MORE INFORMATION

Citation

Bioinformatics. 2013 May 1;29(9):1220-2. doi: 10.1093/bioinformatics/btt122. Epub 2013 Mar 11.
JAWAMix5: an out-of-core HDF5-based java implementation of whole-genome association studies using mixed models.
Long Q, Zhang Q, Vilhjalmsson BJ, Forai P, Seren ü, Nordborg M.

fastLSA 1.0 – Implementation of the Local Similarity Analysis

fastLSA 1.0

:: DESCRIPTION

fastLSA is a new implementation of the Local Similarity Analysis (LSA) algorithm that approximates the detection of significant LSA results using an asymptotic upper bound. Making only the very standard assumptions (independent and identically distributed data, finite variance, asymptotic data size) fastLSA expands some of the boundaries imposed by previous implementations. Written in optimized C, and utilizing POSIX threads, fastLSA is a software package can calculate pairwise LSA statistics and p-value bounds for ten thousand time series with time-steps measuring in the thousands.

::DEVELOPER

Hallam Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / WIndows /MacOsX
  • G++

:: DOWNLOAD

 fastLSA

:: MORE INFORMATION

Citation

BMC Genomics. 2013;14 Suppl 1:S3. doi: 10.1186/1471-2164-14-S1-S3. Epub 2013 Jan 21.
Expanding the boundaries of local similarity analysis.
Durno WE, Hanson NW, Konwar KM, Hallam SJ.

Jevtrace 3.16b – Implementation of Evolutionary Trace

Jevtrace 3.16b

:: DESCRIPTION

Jevtrace is a Java implementation of the evolutionary trace method. The software expands on the evolutionary trace by allowing manipulation of the input data and parameters of analysis, and presents a number of novel tree inspired analysis of protein families. Jevtrace includes a multivalent graphical browser for multiple sequence alignment, phylogeny, and structure, as well as underlying object and algorithmic infrastructure.

::DEVELOPER

Marcin Joachimiak

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / MacOS
  • Java

:: DOWNLOAD

Jevtrace

:: MORE INFORMATION

Citation:

Marcin P Joachimiak and Fred E Cohen
JEvTrace: refinement and variations of the evolutionary trace in JAVA
Genome Biology 2002, 3:research0077-research0077.12