Tag: Metabolic Network

CNApy 1.0.6 – Integrated Environment for Metabolic Network analysis

CNApy 1.0.6

:: DESCRIPTION

CNApy is an open source cross-platform desktop application written in Python, which offers a state-of-the-art graphical front-end for the intuitive analysis of metabolic networks with COBRA methods.

::DEVELOPER

CNApy Organization

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows
  • Python

:: DOWNLOAD

CNApy

:: MORE INFORMATION

Citation:

Thiele S, von Kamp A, Bekiaris PS, Schneider P, Klamt S.
CNApy: a CellNetAnalyzer GUI in Python for Analyzing and Designing Metabolic Networks.
Bioinformatics. 2021 Dec 8:btab828. doi: 10.1093/bioinformatics/btab828. Epub ahead of print. PMID: 34878104.

Systrip 1.0 – Investigation of Time-series data in the context of Metabolic Networks

Systrip 1.0

:: DESCRIPTION

Systrip is a visual environment for the analysis of time-series data in the context of biological networks. Systrip gathers bioinformatics and graph theoretical algorithms that can be assembled in different ways to help biologists in their visual mining process.

::DEVELOPER

Romain Bourqui

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

Systrip

:: MORE INFORMATION

MetaViz – Visualization software for Metabolic Network

MetaViz

:: DESCRIPTION

MetaViz enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways.

::DEVELOPER

Romain Bourqui

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 MetaViz

:: MORE INFORMATION

Citation

Romain Bourqui , Ludovic Cottret , Vincent Lacroix , David Auber , Patrick Mary , Marie-France Sagot and Fabien Jourdan
Metabolic network visualization eliminating node redundance and preserving metabolic pathways
BMC Systems Biology 2007, 1:29doi:10.1186/1752-0509-1-29

Rast2Systrip 1.0.4 – Reconstruct and View Metabolic Networks

Rast2Systrip 1.0.4

:: DESCRIPTION

Rast2Systrip reconstructed metabolic networks, and then view the network comparison in Systrip–a Tulip extension. In Systrip, bioinformaticians and biologists can then graphically explore the differences and similarities–side-by-side–in the networks from all levels–globally, from pathways, or between individual metabolites and enzymes.

::DEVELOPER

the Bordeaux Bioinformatics Center

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 Rast2Systrip

:: MORE INFORMATION

FASTCORE 1.0 – Fast Reconstruction of Compact Context-Specific Metabolic Network Models

FASTCORE 1.0

:: DESCRIPTION

FASTCORE is a generic algorithm for reconstructing context-specific metabolic network models from global genome-wide metabolic network models such as Recon X.

::DEVELOPER

Life Sciences Research Unit, University of Luxembourg

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOSX
  • MatLab

:: DOWNLOAD

 FASTCORE

:: MORE INFORMATION

Citation

PLoS Comput Biol. 2014 Jan;10(1):e1003424. doi: 10.1371/journal.pcbi.1003424. Epub 2014 Jan 16.
Fast reconstruction of compact context-specific metabolic network models.
Vlassis N, Pacheco MP, Sauter T

optGpSampler 1.1 – Sampling Constraint-based Genome-scale Metabolic Networks

optGpSampler 1.1

:: DESCRIPTION

OptGpSampler is a parallel implementation of the Artificial Centering Hit-and-Run algorithm. With this tool, you can efficiently sample the steady-state solution space of a metabolic network.

::DEVELOPER

optGpSampler team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows
  • MatLab
  • Python

:: DOWNLOAD

  optGpSampler

:: MORE INFORMATION

Citation

PLoS One. 2014 Feb 14;9(2):e86587. doi: 10.1371/journal.pone.0086587. eCollection 2014.
optGpSampler: an improved tool for uniformly sampling the solution-space of genome-scale metabolic networks.
Megchelenbrink W, Huynen M, Marchiori E

Fast-SL – Identify Synthetic Lethal sets in Metabolic Networks

Fast-SL

:: DESCRIPTION

Fast-SL is an efficient algorithm to identify synthetic lethal gene/reaction sets in genome-scale metabolic models.

::DEVELOPER

Raman Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOSX
  • MatLab

:: DOWNLOAD

 Fast-SL

:: MORE INFORMATION

Citation

Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks.
Pratapa A, Balachandran S, Raman K.
Bioinformatics. 2015 Jun 17. pii: btv352.

AMBIENT 1.3 – Find Active Modules in Metabolic Networks using High-throughput data

AMBIENT 1.3

:: DESCRIPTION

AMBIENT (Active Modules for Bipartite Networks) is a Python module that uses simulated annealing to find areas of a metabolic network (modules) that have some consistent characteristic. AMBIENT does not require predefined pathways and gives highly specific predictions of affected areas of metabolism.

:DEVELOPER

The research in the Theoretical Systems Biology Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Python

:: DOWNLOAD

  AMBIENT

:: MORE INFORMATION

Citation:

AMBIENT: Active Modules for Bipartite Networks–using high-throughput transcriptomic data to dissect metabolic response.
Bryant WA, Sternberg MJ, Pinney JW.
BMC Syst Biol. 2013 Mar 25;7:26. doi: 10.1186/1752-0509-7-26.

Convert2Sbml / Convert2Matlab – Convert Metabolic Network Source files into SBML / MATLAB files

Convert2Sbml / Convert2Matlab

:: DESCRIPTION

Convert2Sbml / Convert2Matlab is the Java tool to convert various metabolic network source files into SBML / MATLAB files.

::DEVELOPER

CSB – Computational Systems Biology Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Mac /  Linux
  • Java

:: DOWNLOAD

Convert2Sbml / Convert2Matlab

:: MORE INFORMATION

RAVEN 2.5.1 – Reconstruction, Analysis, and Visualization of Metabolic Networks Toolbox

RAVEN 2.5.1

:: DESCRIPTION

The RAVEN Toolbox is a complete environment for reconstruction, analysis, simulation, and visualization of GEMs and runs within MATLAB.

:: DEVELOPER

Systems & Synthetic Biology – SYSBIO, Chalmers University of Technology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows
  • Matlab
  • Excel

:: DOWNLOAD

 RAVEN

:: MORE INFORMATION

Citation

Wang H, Marcišauskas S, Sánchez BJ, Domenzain I, Hermansson D, Agren R, Nielsen J, Kerkhoven EJ.
RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor.
PLoS Comput Biol. 2018 Oct 18;14(10):e1006541. doi: 10.1371/journal.pcbi.1006541. PMID: 30335785; PMCID: PMC6207324.

PLoS Comput Biol. 2013;9(3):e1002980. doi: 10.1371/journal.pcbi.1002980. Epub 2013 Mar 21.
The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum.
Agren R1, Liu L, Shoaie S, Vongsangnak W, Nookaew I, Nielsen J.