FRAGSION 1.0 – Protein Fragment Library Generation

FRAGSION 1.0

:: DESCRIPTION

FRAGSION is a database-free method to efficiently generate protein fragment library by sampling from an Input-Output Hidden Markov Model.

::DEVELOPER

Dr. Jianlin Cheng

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX

:: DOWNLOAD

 FRAGSION

:: MORE INFORMATION

Citation

FRAGSION: ultra-fast protein fragment library generation by IOHMM sampling.
Bhattacharya D, Adhikari B, Li J, Cheng J.
Bioinformatics. 2016 Feb 18. pii: btw067

GGL 4.1.2 – Graph Grammar Library

GGL 4.1.2

:: DESCRIPTION

The GGL (Graph Grammar Library) is an object oriented ANSI C++ library to implement and apply graph rewrite systems. It implements a Single Push Out (SPO) approach. The library is highly modular and uses state-of-the-art algorithms and data structures. To this end, it uses the Boost Graph Library (BGL) for the internal graph representation and efficient (sub)graph isomorphism approaches as the VF2 algorithm.

::DEVELOPER

Ivo Hofacker

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 GGL

:: MORE INFORMATION

Citation

Christoph Flamm, Alexander Ullrich, Heinz Ekker, Martin Mann, Daniel H?gerl, Markus Rohrschneider, Sebastian Sauer, Gerik Scheuermann, Konstantin Klemm, Ivo L. Hofacker, Peter F. Stadler
Evolution of Metabolic Networks: A Computational Framework.
J Sys Chem 1:4, 2010.

OpenMM 7.4 / PyOpenMM 4.0 – Library for Molecular Modeling Simulation

OpenMM 7.4 / PyOpenMM 4.0

:: DESCRIPTION

OpenMM is a library which provides tools for modern molecular modeling simulation. As a library it can be hooked into any code, allowing that code to do molecular modeling with minimal extra coding.

PyOpenMM is a python API that wraps the OpenMM library.

::DEVELOPER

OpenMM Team , PyOpenMM team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Mac OsX/  Linux
  • Python

:: DOWNLOAD

OpenMM , PyOpenMM

:: MORE INFORMATION

Citation

M. S. Friedrichs, P. Eastman, V. Vaidyanathan, M. Houston, S. LeGrand, A. L. Beberg, D. L. Ensign, C. M. Bruns, V. S. Pande.
Accelerating Molecular Dynamic Simulation on Graphics Processing Units.
J. Comp. Chem., 30(6):864-872 (2009)

InSilicoSpectro 1.3.24 – Open-source Proteomics Library

InSilicoSpectro 1.3.24

:: DESCRIPTION

InSilicoSpectro is a proteomics open-source project,aimed at implementing recurrent computations that are necessary for proteomics data analysis.

::DEVELOPER

Alexandre Masselot

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/Windows
  • Perl

:: DOWNLOAD

 InSilicoSpectro

:: MORE INFORMATION

Citation

J Proteome Res. 2006 Mar;5(3):619-24.
InSilicoSpectro: an open-source proteomics library.
Colinge J, Masselot A, Carbonell P, Appel RD.

GDL 1.1.0 – Genetic Data analysis Library

GDL 1.1.0

:: DESCRIPTION

The GDL (Genetic Data analysis Library) is a dynamic C library that aims at providing low level and high level Application Programming Interface (API) to manage and analysis various genetic and genomic data types.

::DEVELOPER

Jean-Baptiste Veyrieras

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • C Compiler

:: DOWNLOAD

 GDL

:: MORE INFORMATION

SSPcompare – Takes a Library of known RNA Sequence-structure Pairs

SSPcompare

:: DESCRIPTION

SSPcompare is a modest tool that takes a library of known sequence-structure pairs, e.g. Andronescu et al. (2008), and predictions by different algorithms and produces tables for easy comparison of different programs. It was written to automate the rather tedious procedure of comparing and testing different programs. The library behind this tool can be of interest if you want to train folding algorithms and need a way to quickly ascertain training success.

::DEVELOPER

Ivo Hofacker

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 SSPcompare

:: MORE INFORMATION

Citation

Höner zu Siederdissen, Christian, Stephan H. Bernhart, Peter F. Stadler, and Ivo L. Hofacker. 2011.
A Folding Algorithm for Extended RNA Secondary Structures. 
Bioinformatics 27: 129–36.

CGL 0.08 – Library designed to Facilitate the use of Genome Annotation

CGL 0.08

:: DESCRIPTION

CGL (Comparitive Genomics Library) is a software library designed to facilitate the use of genome annotations as substrates for computation and experimentation.The purpose of CGL is to provide an informatics infrastructure for a laboratory, department, or research institute engaged in the large-scale analysis of genomes and their annotations.

::DEVELOPER

Yandell Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 CGL

:: MORE INFORMATION

Citation:

Mark Yandell, et al.
Large-Scale Trends in the Evolution of Gene Structures within 11 Animal Genomes
PLoS Comput Biol. 2006 March; 2(3): e15.

Genoman – A Library for Accessing and Manipulating Genome Annotation data

Genoman

:: DESCRIPTION

Genoman (short for genome analysis) is an object-oriented Perl library for accessing and manipulating genome annotation data (e.g. genomic locations of genes and other features, alignments of transcript sequences to a genome, and alignments between different genomes). Genoman defines a set of classes for representing such data. The classes are designed to be flexible and sufficiently efficient to allow their use in analysis pipelines for dealing with large data sets. The library is designed to allow data retrieval from different types of files and databases in a consistent manner, into objects of the same classes. Genoman can be supplemented with custom-written database interface classes for accessing particular databases.

::DEVELOPER

Pär Engström

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 Genoman

:: MORE INFORMATION

parredHMMlib 1.0 – Library for Hardware Accelerated HMM Parallelizing Analysis

parredHMMlib 1.0

:: DESCRIPTION

parredHMMlib is a C++ library implementing the parredForward and parredViterbi algorithms for multi-core CPUs, parallelizing analysis of hidden Markov models with small state spaces.

::DEVELOPER

Andreas Sand.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 parredHMMlib

:: MORE INFORMATION

Citation

Nielsen, J.; Sand, A.;
Algorithms for a Parallel Implementation of Hidden Markov Models with a Small State Space
Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium