Browsing by Author "Klipp, Edda"
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- Minimum Information About a Simulation Experiment (MIASE)Waltemath, Dagmar; Adams, Richard; Beard, Daniel A.; Bergmann, Frank T.; Bhalla, Upinder S.; Britten, Randall; Chelliah, Vijayalakshmi; Cooling, Michael T.; Cooper, Jonathan; Crampin, Edmund J.; Garny, Alan; Hoops, Stefan; Hucka, Michael; Hunger, Peter; Klipp, Edda; Laibe, Camille; Miller, Andrew K.; Moraru, Ion; Nickerson, David; Nielsen, Poul; Nikolski, Macha; Sahle, Sven; Sauro, Herbert M.; Schmidt, Henning; Snoep, Jacky L.; Tolle, Dominic; Wolkenhauer, Olaf; Le Novère, Nicolas (Public Library of Science, 2011-04-28)Reproducibility of experiments is a basic requirement for science. Minimum Information (MI) guidelines have proved a helpful means of enabling reuse of existing work in modern biology. The Minimum Information Required in the Annotation of Models (MIRIAM) guidelines promote the exchange and reuse of biochemical computational models. However, information about a model alone is not sufficient to enable its efficient reuse in a computational setting. Advanced numerical algorithms and complex modeling workflows used in modern computational biology make reproduction of simulations difficult. It is therefore essential to define the core information necessary to perform simulations of those models. The Minimum Information About a Simulation Experiment (MIASE, Glossary in Box 1) describes the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE allows for the reproduction of any simulation experiment. The provision of this information, along with a set of required models, guarantees that the simulation experiment represents the intention of the original authors. Following MIASE guidelines will thus improve the quality of scientific reporting, and will also allow collaborative, more distributed efforts in computational modeling and simulation of biological processes.
- Systematic Construction of Kinetic Models from Genome-Scale Metabolic NetworksStanford, Natalie J.; Lubitz, Timo; Smallbone, Kieran; Klipp, Edda; Mendes, Pedro; Liebermeister, Wolfram (PLOS, 2013-09-14)The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.