Paint4Net: COBRA Toolbox extension for visualization of stoichiometric models of metabolism

Biosystems ◽  
2012 ◽  
Vol 109 (2) ◽  
pp. 233-239 ◽  
Author(s):  
Andrejs Kostromins ◽  
Egils Stalidzans
2015 ◽  
Vol 11 (4) ◽  
pp. e1004166 ◽  
Author(s):  
Timo R. Maarleveld ◽  
Meike T. Wortel ◽  
Brett G. Olivier ◽  
Bas Teusink ◽  
Frank J. Bruggeman

2007 ◽  
Vol 132 (4) ◽  
pp. 405-417 ◽  
Author(s):  
Guido Melzer ◽  
Alex Dalpiaz ◽  
Andreas Grote ◽  
Martin Kucklick ◽  
Yvonne Göcke ◽  
...  

Author(s):  
Almut Heinken ◽  
Stefanía Magnúsdóttir ◽  
Ronan M T Fleming ◽  
Ines Thiele

Abstract Motivation Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account. Results We developed DEMETER, a COBRA Toolbox extension, that enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data, and refinement of pathways based on manually refined genome annotations. Availability DEMETER and tutorials are freely available at https://github.com/opencobra.


2017 ◽  
Vol 4 (12) ◽  
pp. 170770 ◽  
Author(s):  
Ryan E. Sherman ◽  
Priyanka Roy Chowdhury ◽  
Kristina D. Baker ◽  
Lawrence J. Weider ◽  
Punidan D. Jeyasingh

The framework ecological stoichiometry uses elemental composition of species to make predictions about growth and competitive ability in defined elemental supply conditions. Although intraspecific differences in stoichiometry have been observed, we have yet to understand the mechanisms generating and maintaining such variation. We used variation in phosphorus (P) content within a Daphnia species to test the extent to which %P can explain variation in growth and competition. Further, we measured 33 P kinetics (acquisition, assimilation, incorporation and retention) to understand the extent to which such variables improved predictions. Genotypes showed significant variation in P content, 33 P kinetics and growth rate. P content alone was a poor predictor of growth rate and competitive ability. While most genotypes exhibited the typical growth penalty under P limitation, a few varied little in growth between P diets. These observations indicate that some genotypes can maintain growth under P-limited conditions by altering P use, suggesting that decomposing P content of an individual into physiological components of P kinetics will improve stoichiometric models. More generally, attention to the interplay between nutrient content and nutrient-use is required to make inferences regarding the success of genotypes in defined conditions of nutrient supply.


2018 ◽  
Vol 46 (2) ◽  
pp. 403-412 ◽  
Author(s):  
Antonella Succurro ◽  
Oliver Ebenhöh

Understanding microbial ecosystems means unlocking the path toward a deeper knowledge of the fundamental mechanisms of life. Engineered microbial communities are also extremely relevant to tackling some of today's grand societal challenges. Advanced meta-omics experimental techniques provide crucial insights into microbial communities, but have been so far mostly used for descriptive, exploratory approaches to answer the initial ‘who is there?’ question. An ecosystem is a complex network of dynamic spatio-temporal interactions among organisms as well as between organisms and the environment. Mathematical models with their abstraction capability are essential to capture the underlying phenomena and connect the different scales at which these systems act. Differential equation models and constraint-based stoichiometric models are deterministic approaches that can successfully provide a macroscopic description of the outcome from microscopic behaviors. In this mini-review, we present classical and recent applications of these modeling methods and illustrate the potential of their integration. Indeed, approaches that can capture multiple scales are needed in order to understand emergent patterns in ecosystems and their dynamics regulated by different spatio-temporal phenomena. We finally discuss promising examples of methods proposing the integration of differential equations with constraint-based stoichiometric models and argue that more work is needed in this direction.


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