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

2007 ◽  
Vol 2 (3) ◽  
pp. 727-738 ◽  
Author(s):  
Scott A Becker ◽  
Adam M Feist ◽  
Monica L Mo ◽  
Gregory Hannum ◽  
Bernhard Ø Palsson ◽  
...  
2011 ◽  
Vol 6 (9) ◽  
pp. 1290-1307 ◽  
Author(s):  
Jan Schellenberger ◽  
Richard Que ◽  
Ronan M T Fleming ◽  
Ines Thiele ◽  
Jeffrey D Orth ◽  
...  

2016 ◽  
Author(s):  
R.P. Vivek-Ananth ◽  
Areejit Samal

AbstractA major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks.


2019 ◽  
Vol 14 (3) ◽  
pp. 639-702 ◽  
Author(s):  
Laurent Heirendt ◽  
Sylvain Arreckx ◽  
Thomas Pfau ◽  
Sebastián N. Mendoza ◽  
Anne Richelle ◽  
...  

2021 ◽  
Author(s):  
Marc Griesemer ◽  
Ali Navid

Multi-objective Optimization (MO) is an important tool for quantitative examination of the trade-offs faced by biological organisms. Using genome-scale constraint-based models of metabolism (GSMs),Multi-Objective Flux Analysis (MOFA) allows MO analyses of trade-offs among key biological tasks. The leading software package for conducting a plethora of different types of constraint-based analyses using GSMs is the COBRA Toolbox for MATLAB. We have developed a new add-on tool for this toolbox using Normalized Normal Constraint (NNC) that performs MOFA for a number of objectives only limited by computation power (n≤10). This development will facilitate MOFA analyses by COBRA's large user base and allow greater multi-faceted examination of metabolic trade-offs in complicated biological systems. Availability and Implementation: The MOFA software is freely available for download from https://bbs.llnl.gov under the GPL v2 license. The program runs on MATLAB with the COBRA software on Windows, Linux, and MacOS. It includes a detailed manual explaining the input and output of a simulation, a listing of the code's functions, and an example MOFA run using a well-curated GSM model of E. coli.


2018 ◽  
Vol 46 (3) ◽  
pp. 130-152
Author(s):  
Dennis S. Kelliher

ABSTRACT When performing predictive durability analyses on tires using finite element methods, it is generally recognized that energy release rate (ERR) is the best measure by which to characterize the fatigue behavior of rubber. By addressing actual cracks in a simulation geometry, ERR provides a more appropriate durability criterion than the strain energy density (SED) of geometries without cracks. If determined as a function of crack length and loading history, and augmented with material crack growth properties, ERR allows for a quantitative prediction of fatigue life. Complications arise, however, from extra steps required to implement the calculation of ERR within the analysis process. This article presents an overview and some details of a method to perform such analyses. The method involves a preprocessing step that automates the creation of a ribbon crack within an axisymmetric-geometry finite element model at a predetermined location. After inflating and expanding to three dimensions to fully load the tire against a surface, full ribbon sections of the crack are then incrementally closed through multiple solution steps, finally achieving complete closure. A postprocessing step is developed to determine ERR as a function of crack length from this enforced crack closure technique. This includes an innovative approach to calculating ERR as the crack length approaches zero.


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