Showing papers by "Federico Morán published in 2011"
TL;DR: Tools-4-Metatool (T4M) is a suite of web-tools, implemented in PERL, which analyses, parses, and manipulates files related to Metatool, and its main goal is to assist the work with Metatools.
Abstract: Tools-4-Metatool (T4M) is a suite of web-tools, implemented in PERL, which analyses, parses, and manipulates files related to Metatool. Its main goal is to assist the work with Metatool. T4M has two major sets of tools: Analysis and Compare. Analysis visualizes the results of Metatool (convex basis, elementary flux modes, and enzyme subsets) and facilitates the study of metabolic networks. It is composed of five tools: MDigraph, MetaMatrix, CBGraph, EMGraph, and SortEM. Compare was developed to compare different Metatool results from different networks. This set consists of: Compara and ComparaSub which compare network subsets providing outputs in different formats and ComparaEM that seeks for identical elementary modes in two metabolic networks. The suite T4M also includes one script that generates Metatool input: CBasis2Metatool, based on a Metatool output file that is filtered by a list of convex basis’ metabolites. Finally, the utility CheckMIn checks the consistency of the Metatool input file. T4M is available at
9 citations
TL;DR: The performance of the proposed GFE-based optimization method is compared to that obtained from minimization of the squared distances between the observed and predicted concentrations obtained by solving the corresponding initial value problem and a new hybrid method that combines advantages from the GFE and traditional approaches is presented.
Abstract: A new approach for parameter estimation in chemical kinetics has been recently proposed (Ross et al. Proc. Natl. Acad. Sci. U.S.A.2010, 107, 12777). It makes use of an optimization criterion based on a Generalized Fisher Equation (GFE). Its utility has been demonstrated with two reaction mechanisms, the chlorite–iodide and Oregonator, which are computationally stiff systems. In this Article, the performance of the GFE-based algorithm is compared to that obtained from minimization of the squared distances between the observed and predicted concentrations obtained by solving the corresponding initial value problem (we call this latter approach “traditional” for simplicity). Comparison of the proposed GFE-based optimization method with the “traditional” one has revealed their differences in performance. This difference can be seen as a trade-off between speed (which favors GFE) and accuracy (which favors the traditional method). The chlorite–iodide and Oregonator systems are again chosen as case studies. An ...
7 citations