scispace - formally typeset
Open AccessJournal ArticleDOI

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

TLDR
The constraint-based reconstruction and analysis toolbox as discussed by the authors is a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraintbased approach and allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules.
Abstract
The manner in which microorganisms utilize their metabolic processes can be predicted using constraint-based analysis of genome-scale metabolic networks. Herein, we present the constraint-based reconstruction and analysis toolbox, a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraint-based approach. Specifically, this software allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules. Functions enabling these calculations are included in the toolbox, allowing a user to input a genome-scale metabolic model distributed in Systems Biology Markup Language format and perform these calculations with just a few lines of code. The results are predictions of cellular behavior that have been verified as accurate in a growing body of research. After software installation, calculation time is minimal, allowing the user to focus on the interpretation of the computational results.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Metabolic network reconstruction of Chlamydomonas offers insight into light‐driven algal metabolism

TL;DR: A genome‐scale metabolic network is reconstructed for this alga and a novel light‐modeling approach is devised that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux.
Journal ArticleDOI

Restoring the sense of touch with a prosthetic hand through a brain interface.

TL;DR: This work proposes that the timing of contact events can be signaled through phasic intracortical microstimulation at the onset and offset of object contact that mimics the ubiquitous on and off responses observed in primary somatosensory cortex to complement slowly varying pressure-related feedback.
Journal ArticleDOI

Microbial laboratory evolution in the era of genome‐scale science

TL;DR: This work reviews studies centered on four central themes of laboratory evolution studies: the genetic basis of adaptation; the importance of mutations to genes that encode regulatory hubs; the view of adaptive evolution as an optimization process; and the dynamics with which laboratory populations evolve.
References
More filters
Journal ArticleDOI

Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Journal ArticleDOI

KEGG: Kyoto Encyclopedia of Genes and Genomes

TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Journal ArticleDOI

The KEGG resource for deciphering the genome

TL;DR: A knowledge-based approach for network prediction is developed, which is to predict, given a complete set of genes in the genome, the protein interaction networks that are responsible for various cellular processes.
Journal ArticleDOI

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

TL;DR: This work summarizes the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks, a software-independent language for describing models common to research in many areas of computational biology.
Related Papers (5)