Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics

Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifi...
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Autor*in:	Surovtsova, Irina [verfasserIn] Simus, Natalia Hübner, Katrin Sahle, Sven Kummer, Ursula

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2012

Schlagwörter:	Fast Mode Dynamic Regime Oscillatory Regime Quasi Equilibrium Fast Time Scale

Anmerkung:	© Surovtsova et al; licensee BioMed Central Ltd. 2012

Übergeordnetes Werk:	Enthalten in: BMC systems biology - London : BioMed Central, 2007, 6(2012), 1 vom: 05. März
Übergeordnetes Werk:	volume:6 ; year:2012 ; number:1 ; day:05 ; month:03

Links:	Volltext

DOI / URN:	10.1186/1752-0509-6-14

Katalog-ID:	SPR028413148

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520			\|a Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org.
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spelling	10.1186/1752-0509-6-14 doi (DE-627)SPR028413148 (SPR)1752-0509-6-14-e DE-627 ger DE-627 rakwb eng Surovtsova, Irina verfasserin aut Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Surovtsova et al; licensee BioMed Central Ltd. 2012 Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org. Fast Mode (dpeaa)DE-He213 Dynamic Regime (dpeaa)DE-He213 Oscillatory Regime (dpeaa)DE-He213 Quasi Equilibrium (dpeaa)DE-He213 Fast Time Scale (dpeaa)DE-He213 Simus, Natalia aut Hübner, Katrin aut Sahle, Sven aut Kummer, Ursula aut Enthalten in BMC systems biology London : BioMed Central, 2007 6(2012), 1 vom: 05. März (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:6 year:2012 number:1 day:05 month:03 https://dx.doi.org/10.1186/1752-0509-6-14 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2012 1 05 03
allfields_unstemmed	10.1186/1752-0509-6-14 doi (DE-627)SPR028413148 (SPR)1752-0509-6-14-e DE-627 ger DE-627 rakwb eng Surovtsova, Irina verfasserin aut Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Surovtsova et al; licensee BioMed Central Ltd. 2012 Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org. Fast Mode (dpeaa)DE-He213 Dynamic Regime (dpeaa)DE-He213 Oscillatory Regime (dpeaa)DE-He213 Quasi Equilibrium (dpeaa)DE-He213 Fast Time Scale (dpeaa)DE-He213 Simus, Natalia aut Hübner, Katrin aut Sahle, Sven aut Kummer, Ursula aut Enthalten in BMC systems biology London : BioMed Central, 2007 6(2012), 1 vom: 05. März (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:6 year:2012 number:1 day:05 month:03 https://dx.doi.org/10.1186/1752-0509-6-14 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2012 1 05 03
allfieldsGer	10.1186/1752-0509-6-14 doi (DE-627)SPR028413148 (SPR)1752-0509-6-14-e DE-627 ger DE-627 rakwb eng Surovtsova, Irina verfasserin aut Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Surovtsova et al; licensee BioMed Central Ltd. 2012 Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org. Fast Mode (dpeaa)DE-He213 Dynamic Regime (dpeaa)DE-He213 Oscillatory Regime (dpeaa)DE-He213 Quasi Equilibrium (dpeaa)DE-He213 Fast Time Scale (dpeaa)DE-He213 Simus, Natalia aut Hübner, Katrin aut Sahle, Sven aut Kummer, Ursula aut Enthalten in BMC systems biology London : BioMed Central, 2007 6(2012), 1 vom: 05. März (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:6 year:2012 number:1 day:05 month:03 https://dx.doi.org/10.1186/1752-0509-6-14 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2012 1 05 03
allfieldsSound	10.1186/1752-0509-6-14 doi (DE-627)SPR028413148 (SPR)1752-0509-6-14-e DE-627 ger DE-627 rakwb eng Surovtsova, Irina verfasserin aut Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Surovtsova et al; licensee BioMed Central Ltd. 2012 Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org. Fast Mode (dpeaa)DE-He213 Dynamic Regime (dpeaa)DE-He213 Oscillatory Regime (dpeaa)DE-He213 Quasi Equilibrium (dpeaa)DE-He213 Fast Time Scale (dpeaa)DE-He213 Simus, Natalia aut Hübner, Katrin aut Sahle, Sven aut Kummer, Ursula aut Enthalten in BMC systems biology London : BioMed Central, 2007 6(2012), 1 vom: 05. März (DE-627)522897126 (DE-600)2265490-2 1752-0509 nnns volume:6 year:2012 number:1 day:05 month:03 https://dx.doi.org/10.1186/1752-0509-6-14 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2012 1 05 03
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authorswithroles_txt_mv	Surovtsova, Irina @@aut@@ Simus, Natalia @@aut@@ Hübner, Katrin @@aut@@ Sahle, Sven @@aut@@ Kummer, Ursula @@aut@@
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We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. 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author	Surovtsova, Irina
spellingShingle	Surovtsova, Irina misc Fast Mode misc Dynamic Regime misc Oscillatory Regime misc Quasi Equilibrium misc Fast Time Scale Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
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topic_title	Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics Fast Mode (dpeaa)DE-He213 Dynamic Regime (dpeaa)DE-He213 Oscillatory Regime (dpeaa)DE-He213 Quasi Equilibrium (dpeaa)DE-He213 Fast Time Scale (dpeaa)DE-He213
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title	Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
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title_full	Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
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title_sort	simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
title_auth	Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
abstract	Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org. © Surovtsova et al; licensee BioMed Central Ltd. 2012
abstractGer	Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org. © Surovtsova et al; licensee BioMed Central Ltd. 2012
abstract_unstemmed	Background Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms. Results We have developed a strategy based on the Computational Singular Perturbation (CSP) method which can be used to perform a "biochemically-driven" model reduction of even large and complex kinetic ODE systems. We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. COPASI is freely available at http://www.copasi.org. © Surovtsova et al; licensee BioMed Central Ltd. 2012
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title_short	Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
url	https://dx.doi.org/10.1186/1752-0509-6-14
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author2	Simus, Natalia Hübner, Katrin Sahle, Sven Kummer, Ursula
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We provide an implementation of the original CSP algorithm in COPASI (a COmplex PAthway SImulator) and applied the strategy to two example models of different degree of complexity - a simple one-enzyme system and a full-scale model of yeast glycolysis. Conclusion The results show the usefulness of the method for model simplification purposes as well as for analyzing fundamental biochemical mechanisms. 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Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics

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