Literature DB >> 19425122

ModelMage: a tool for automatic model generation, selection and management.

Max Flöttmann1, Jörg Schaber, Stephan Hoops, Edda Klipp, Pedro Mendes.   

Abstract

Mathematical modeling of biological systems usually involves implementing, simulating, and discriminating several candidate models that represent alternative hypotheses. Generating and managing these candidate models is a tedious and difficult task and can easily lead to errors. ModelMage is a tool that facilitates management of candidate models. It is designed for the easy and rapid development, generation, simulation, and discrimination of candidate models. The main idea of the program is to automatically create a defined set of model alternatives from a single master model. The user provides only one SBML-model and a set of directives from which the candidate models are created by leaving out species, modifiers or reactions. After generating models the software can automatically fit all these models to the data and provides a ranking for model selection, in case data is available. In contrast to other model generation programs, ModelMage aims at generating only a limited set of models that the user can precisely define. ModelMage uses COPASI as a simulation and optimization engine. Thus, all simulation and optimization features of COPASI are readily incorporated. ModelMage can be downloaded from http://sysbio.molgen.mpg.de/modelmage and is distributed as free software.

Mesh:

Year:  2008        PMID: 19425122

Source DB:  PubMed          Journal:  Genome Inform        ISSN: 0919-9454


  9 in total

Review 1.  Bridging the gaps in systems biology.

Authors:  Marija Cvijovic; Joachim Almquist; Jonas Hagmar; Stefan Hohmann; Hans-Michael Kaltenbach; Edda Klipp; Marcus Krantz; Pedro Mendes; Sven Nelander; Jens Nielsen; Andrea Pagnani; Natasa Przulj; Andreas Raue; Jörg Stelling; Szymon Stoma; Frank Tobin; Judith A H Wodke; Riccardo Zecchina; Mats Jirstrand
Journal:  Mol Genet Genomics       Date:  2014-04-13       Impact factor: 3.291

2.  Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast.

Authors:  Jörg Schaber; Rodrigo Baltanas; Alan Bush; Edda Klipp; Alejandro Colman-Lerner
Journal:  Mol Syst Biol       Date:  2012       Impact factor: 11.429

3.  Automated ensemble modeling with modelMaGe: analyzing feedback mechanisms in the Sho1 branch of the HOG pathway.

Authors:  Jörg Schaber; Max Flöttmann; Jian Li; Carl-Fredrik Tiger; Stefan Hohmann; Edda Klipp
Journal:  PLoS One       Date:  2011-03-30       Impact factor: 3.240

4.  A helminth immunomodulator exploits host signaling events to regulate cytokine production in macrophages.

Authors:  Christian Klotz; Thomas Ziegler; Ana Sofia Figueiredo; Sebastian Rausch; Matthew R Hepworth; Nadja Obsivac; Christine Sers; Roland Lang; Peter Hammerstein; Richard Lucius; Susanne Hartmann
Journal:  PLoS Pathog       Date:  2011-01-06       Impact factor: 6.823

5.  PyCoTools: a Python toolbox for COPASI.

Authors:  Ciaran M Welsh; Nicola Fullard; Carole J Proctor; Alvaro Martinez-Guimera; Robert J Isfort; Charles C Bascom; Ryan Tasseff; Stefan A Przyborski; Daryl P Shanley
Journal:  Bioinformatics       Date:  2018-11-01       Impact factor: 6.937

6.  Molecular noise filtering in the β-adrenergic signaling network by phospholamban pentamers.

Authors:  Daniel Koch; Alexander Alexandrovich; Florian Funk; Ay Lin Kho; Joachim P Schmitt; Mathias Gautel
Journal:  Cell Rep       Date:  2021-07-27       Impact factor: 9.995

7.  Nested autoinhibitory feedbacks alter the resistance of homeostatic adaptive biochemical networks.

Authors:  Jörg Schaber; Anastasiya Lapytsko; Dietrich Flockerzi
Journal:  J R Soc Interface       Date:  2013-12-04       Impact factor: 4.118

8.  Topological augmentation to infer hidden processes in biological systems.

Authors:  Mikael Sunnåker; Elias Zamora-Sillero; Adrián López García de Lomana; Florian Rudroff; Uwe Sauer; Joerg Stelling; Andreas Wagner
Journal:  Bioinformatics       Date:  2013-12-02       Impact factor: 6.937

9.  How informative is your kinetic model?: using resampling methods for model invalidation.

Authors:  Dicle Hasdemir; Huub C J Hoefsloot; Johan A Westerhuis; Age K Smilde
Journal:  BMC Syst Biol       Date:  2014-05-22
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.