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1. SBML Level 3: an extensible format for the exchange and reuse of biological models.

Author

Keating, Sarah M, Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, SBML Level 3 Community members, Keating, Sarah M, Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, and SBML Level 3 Community members

Abstract

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Published
2020

2. SBML Level 3: an extensible format for the exchange and reuse of biological models.

Author

Keating, Sarah M, Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, SBML Level 3 Community members, Keating, Sarah M, Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, and SBML Level 3 Community members

Abstract

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Published
2020

3. SBML Level 3: an extensible format for the exchange and reuse of biological models.

Author

Keating, Sarah M, Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, SBML Level 3 Community members, Keating, Sarah M, Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, and SBML Level 3 Community members

Abstract

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Published
2020

4. SBML Level 3: an extensible format for the exchange and reuse of biological models

Author

Computer Science, Keating, Sarah M., Waltemath, Dagmar, Koenig, Matthias, Zhang, Fengkai, Draeger, Andreas, Chaouiya, Claudine, Bergmann, Frank T., Finney, Andrew, Gillespie, Colin S., Helikar, Tomas, Hoops, Stefan, Malik-Sheriff, Rahuman S., Moodie, Stuart L., Moraru, Ion I., Myers, Chris J., Naldi, Aurelien, Olivier, Brett G., Sahle, Sven, Schaff, James C., Smith, Lucian P., Swat, Maciej J., Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J., Blinov, Michael L., Begley, Kimberly, Faeder, James R., Gomez, Harold F., Hamm, Thomas M., Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L., Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J., Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A., Shapiro, Bruce E., Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M., Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C., Hucka, Michael, Computer Science, Keating, Sarah M., Waltemath, Dagmar, Koenig, Matthias, Zhang, Fengkai, Draeger, Andreas, Chaouiya, Claudine, Bergmann, Frank T., Finney, Andrew, Gillespie, Colin S., Helikar, Tomas, Hoops, Stefan, Malik-Sheriff, Rahuman S., Moodie, Stuart L., Moraru, Ion I., Myers, Chris J., Naldi, Aurelien, Olivier, Brett G., Sahle, Sven, Schaff, James C., Smith, Lucian P., Swat, Maciej J., Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J., Blinov, Michael L., Begley, Kimberly, Faeder, James R., Gomez, Harold F., Hamm, Thomas M., Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L., Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J., Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A., Shapiro, Bruce E., Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M., Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C., and Hucka, Michael

Abstract

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developedSBMLLevel 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades ofSBMLand a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and howSBMLLevel 3 provides the foundation needed to support this evolution.

Published
2020

5. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.

Author

Heirendt, Laurent, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N, Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S, Wachowiak, Jacek, Keating, Sarah M, Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu HJ, Aurich, Maike K, Clancy, Catherine M, Modamio, Jennifer, Sauls, John T, Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C, Valcarcel, Luis V, Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M, Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T, Oliveira, Miguel AP, Vuong, Phan T, El Assal, Lemmer P, Kuperstein, Inna, Zinovyev, Andrei, Hinton, H Scott, Bryant, William A, Aragón Artacho, Francisco J, Planes, Francisco J, Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A, Maranas, Costas D, Lewis, Nathan E, Sauter, Thomas, Palsson, Bernhard Ø, Thiele, Ines, Fleming, Ronan MT, Heirendt, Laurent, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N, Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S, Wachowiak, Jacek, Keating, Sarah M, Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu HJ, Aurich, Maike K, Clancy, Catherine M, Modamio, Jennifer, Sauls, John T, Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C, Valcarcel, Luis V, Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M, Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T, Oliveira, Miguel AP, Vuong, Phan T, El Assal, Lemmer P, Kuperstein, Inna, Zinovyev, Andrei, Hinton, H Scott, Bryant, William A, Aragón Artacho, Francisco J, Planes, Francisco J, Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A, Maranas, Costas D, Lewis, Nathan E, Sauter, Thomas, Palsson, Bernhard Ø, Thiele, Ines, and Fleming, Ronan MT

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019

6. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

Author

Universidad de Alicante. Departamento de Matemáticas, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco Javier, Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, Fleming, Ronan M.T., Universidad de Alicante. Departamento de Matemáticas, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco Javier, Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, and Fleming, Ronan M.T.

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019

7. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.

Author

Heirendt, Laurent, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N, Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S, Wachowiak, Jacek, Keating, Sarah M, Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu HJ, Aurich, Maike K, Clancy, Catherine M, Modamio, Jennifer, Sauls, John T, Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C, Valcarcel, Luis V, Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M, Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T, Oliveira, Miguel AP, Vuong, Phan T, El Assal, Lemmer P, Kuperstein, Inna, Zinovyev, Andrei, Hinton, H Scott, Bryant, William A, Aragón Artacho, Francisco J, Planes, Francisco J, Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A, Maranas, Costas D, Lewis, Nathan E, Sauter, Thomas, Palsson, Bernhard Ø, Thiele, Ines, Fleming, Ronan MT, Heirendt, Laurent, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N, Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S, Wachowiak, Jacek, Keating, Sarah M, Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu HJ, Aurich, Maike K, Clancy, Catherine M, Modamio, Jennifer, Sauls, John T, Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C, Valcarcel, Luis V, Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M, Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T, Oliveira, Miguel AP, Vuong, Phan T, El Assal, Lemmer P, Kuperstein, Inna, Zinovyev, Andrei, Hinton, H Scott, Bryant, William A, Aragón Artacho, Francisco J, Planes, Francisco J, Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A, Maranas, Costas D, Lewis, Nathan E, Sauter, Thomas, Palsson, Bernhard Ø, Thiele, Ines, and Fleming, Ronan MT

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019

8. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.

Author

Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastian N., Richelle, Anne, Heinken, Almut Katrin, Haraldsdottir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdottir, Stefania, Ng, Chiam Yu, Preciat, German, Zagare, Alise, Chan, Siu H. J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana Charles, Valcarcel, Luis V., Apaolaza, Inigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragon Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard O., Thiele, Ines, Fleming, Ronan M. T., Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastian N., Richelle, Anne, Heinken, Almut Katrin, Haraldsdottir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdottir, Stefania, Ng, Chiam Yu, Preciat, German, Zagare, Alise, Chan, Siu H. J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana Charles, Valcarcel, Luis V., Apaolaza, Inigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragon Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard O., Thiele, Ines, and Fleming, Ronan M. T.

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019

9. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.

Author

Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastian N., Richelle, Anne, Heinken, Almut Katrin, Haraldsdottir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdottir, Stefania, Ng, Chiam Yu, Preciat, German, Zagare, Alise, Chan, Siu H. J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana Charles, Valcarcel, Luis V., Apaolaza, Inigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragon Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard O., Thiele, Ines, Fleming, Ronan M. T., Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastian N., Richelle, Anne, Heinken, Almut Katrin, Haraldsdottir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdottir, Stefania, Ng, Chiam Yu, Preciat, German, Zagare, Alise, Chan, Siu H. J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana Charles, Valcarcel, Luis V., Apaolaza, Inigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragon Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard O., Thiele, Ines, and Fleming, Ronan M. T.

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019

10. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

Author

Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard, Thiele, Ines, Fleming, Ronan M.T., Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard, Thiele, Ines, and Fleming, Ronan M.T.

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019
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11. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

Author

Universidad de Alicante. Departamento de Matemáticas, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco Javier, Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, Fleming, Ronan M.T., Universidad de Alicante. Departamento de Matemáticas, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco Javier, Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, and Fleming, Ronan M.T.

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019

12. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

Author

Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastian N., Richelle, Anne, Heinken, Almut, Haraldsdottir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdottir, Stefania, Ng, Chiam Yu, Preciat, German, Zagare, Alise, Chan, Siu Hung Joshua, Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Inigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragon Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard O., Thiele, Ines, Fleming, Ronan M. T., Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastian N., Richelle, Anne, Heinken, Almut, Haraldsdottir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdottir, Stefania, Ng, Chiam Yu, Preciat, German, Zagare, Alise, Chan, Siu Hung Joshua, Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Inigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragon Artacho, Francisco J., Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard O., Thiele, Ines, and Fleming, Ronan M. T.

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

Published
2019

13. SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools

Author

Chaouiya, Claudine, Chaouiya, Claudine, Bérenguier, Duncan, Keating, Sarah M, Naldi, Aurélien, van Iersel, Martijn P, Rodriguez, Nicolas, Dräger, Andreas, Büchel, Finja, Cokelaer, Thomas, Kowal, Bryan, Wicks, Benjamin, Gonçalves, Emanuel, Dorier, Julien, Page, Michel, Monteiro, Pedro T, von Kamp, Axel, Xenarios, Ioannis, de Jong, Hidde, Hucka, Michael, Klamt, Steffen, Thieffry, Denis, Le Novère, Nicolas, Saez-Rodriguez, Julio, Helikar, Tomáš, Chaouiya, Claudine, Chaouiya, Claudine, Bérenguier, Duncan, Keating, Sarah M, Naldi, Aurélien, van Iersel, Martijn P, Rodriguez, Nicolas, Dräger, Andreas, Büchel, Finja, Cokelaer, Thomas, Kowal, Bryan, Wicks, Benjamin, Gonçalves, Emanuel, Dorier, Julien, Page, Michel, Monteiro, Pedro T, von Kamp, Axel, Xenarios, Ioannis, de Jong, Hidde, Hucka, Michael, Klamt, Steffen, Thieffry, Denis, Le Novère, Nicolas, Saez-Rodriguez, Julio, and Helikar, Tomáš

Abstract

Background Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. Results We present the Systems Biology Markup Language (SBML) Qualitative Models Package (“qual”), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. Conclusions SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Published
2013

14. SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools

Author

Chaouiya, Claudine, Chaouiya, Claudine, Bérenguier, Duncan, Keating, Sarah M, Naldi, Aurélien, van Iersel, Martijn P, Rodriguez, Nicolas, Dräger, Andreas, Büchel, Finja, Cokelaer, Thomas, Kowal, Bryan, Wicks, Benjamin, Gonçalves, Emanuel, Dorier, Julien, Page, Michel, Monteiro, Pedro T, von Kamp, Axel, Xenarios, Ioannis, de Jong, Hidde, Hucka, Michael, Klamt, Steffen, Thieffry, Denis, Le Novère, Nicolas, Saez-Rodriguez, Julio, Helikar, Tomáš, Chaouiya, Claudine, Chaouiya, Claudine, Bérenguier, Duncan, Keating, Sarah M, Naldi, Aurélien, van Iersel, Martijn P, Rodriguez, Nicolas, Dräger, Andreas, Büchel, Finja, Cokelaer, Thomas, Kowal, Bryan, Wicks, Benjamin, Gonçalves, Emanuel, Dorier, Julien, Page, Michel, Monteiro, Pedro T, von Kamp, Axel, Xenarios, Ioannis, de Jong, Hidde, Hucka, Michael, Klamt, Steffen, Thieffry, Denis, Le Novère, Nicolas, Saez-Rodriguez, Julio, and Helikar, Tomáš

Abstract

Background Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. Results We present the Systems Biology Markup Language (SBML) Qualitative Models Package (“qual”), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. Conclusions SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Published
2013

15. A profile of today's SBML-compatible software

Author

Hucka, Michael, Bergmann, Frank T., Keating, Sarah M., Smith, Lucian P., Hucka, Michael, Bergmann, Frank T., Keating, Sarah M., and Smith, Lucian P.

Abstract

Computational systems biologists today have a healthy selection of software resources to help them do research. Many software packages, especially those concerned with computational modeling, have adopted SBML (the Systems Biology Markup Language) as a machine-readable format to permit users to exchange models. Our group has a keen interest in understanding the landscape of SBML support. To help us ascertain the state of modern SBML-compatible software, in mid-2011 we initiated a survey of software packages that support SBML. Here we report the preliminary survey results. Based on 81 packages for which we have data so far, we summarize the trends in six areas: (1) What are the major types of functionality offered by the software systems? (2) What mathematical frameworks do they support? (3) What are their SBML-specific capabilities? (4) What other standards do they support besides SBML? (5) What are their characteristics with respect to run-time environments? And finally, (6) what are the availability and licensing terms?

Published
2011

16. The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core

Author

Hucka, Michael, Bergmann, Frank T., Hoops, Stefan, Keating, Sarah M., Sahle, Sven, Schaff, James C., Smith, Lucian P., Wilkinson, Darren J., Hucka, Michael, Bergmann, Frank T., Hoops, Stefan, Keating, Sarah M., Sahle, Sven, Schaff, James C., Smith, Lucian P., and Wilkinson, Darren J.

Abstract

This document defines Version 1 of the Systems Biology Markup Language (SBML) Level 3 Core, an electronic model representation format for systems biology. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. SBML is defined neutrally with respect to programming languages and software encoding; however, it is oriented primarily towards allowing models to be encoded using XML, the eXtensible Markup Language (Bray et al., 2004). This document contains many examples of SBML models written in XML. Formal schemas describing the syntax of SBML, as well as other materials and software, are available from the SBML project web site, http://sbml.org/. The SBML project is not an attempt to define a universal language for representing quantitative models. The rapidly evolving views of biological function, coupled with the vigorous rates at which new computational techniques and individual tools are being developed today, are incompatible with a one-size-fits-all idea of a universal language. A more realistic alternative is to acknowledge the diversity of approaches and methods being explored by different software tool developers, and seek a common intermediate format—a lingua franca—enabling communication of the most essential aspects of the models. The definition of the model description language presented here does not specify how programs should communicate or read/write SBML. We assume that for a simulation program to communicate a model encoded in SBML, the program will have to translate its internal data structures to and from SBML, use a suitable transmission medium and protocol, etc., but these issues are outside the scope of this document.

Published
2010

17. SBML Models and MathSBML

Author

Choi, Sangdun, Shapiro, Bruce E., Finney, Andrew, Hucka, Michael, Bornstein, Benjamin, Funahashi, Akira, Jouraku, Akiya, Keating, Sarah M., Le Novère, Nicolas, Matthews, Joanne, Schilstra, Maria J., Choi, Sangdun, Shapiro, Bruce E., Finney, Andrew, Hucka, Michael, Bornstein, Benjamin, Funahashi, Akira, Jouraku, Akiya, Keating, Sarah M., Le Novère, Nicolas, Matthews, Joanne, and Schilstra, Maria J.

Abstract

MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a tool-neutral, computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation.

Published
2007

18. SBMLToolbox: an SBML toolbox for MATLAB users

Author

Keating, Sarah M., Bornstein, Benjamin J., Finney, Andrew, Hucka, Michael, Keating, Sarah M., Bornstein, Benjamin J., Finney, Andrew, and Hucka, Michael

Abstract

We present SBMLToolbox, a toolbox that facilitates importing and exporting models represented in the Systems Biology Markup Language (SBML) in and out of the MATLAB environment and provides functionality that enables an experienced user of either SBML or MATLAB to combine the computing power of MATLAB with the portability and exchangeability of an SBML model. SBMLToolbox supports all levels and versions of SBML.

Published
2006

19. Software Infrastructure for Effective Communication and Reuse of Computational Models

Author

Szallasi, Zoltan, Stelling, Jörg, Periwal, Vipul, Finney, Andrew, Hucka, Michael, Bornstein, Benjamin J., Keating, Sarah M., Shapiro, Bruce E., Matthews, Joanne, Kovitz, Ben L., Schilstra, Maria J., Funahashi, Akira, Doyle, John, Kitano, Hiroaki, Szallasi, Zoltan, Stelling, Jörg, Periwal, Vipul, Finney, Andrew, Hucka, Michael, Bornstein, Benjamin J., Keating, Sarah M., Shapiro, Bruce E., Matthews, Joanne, Kovitz, Ben L., Schilstra, Maria J., Funahashi, Akira, Doyle, John, and Kitano, Hiroaki

Abstract

Until recently, the majority of computational models in biology were implemented in custom programs and published as statements of the underlying mathematics. However, to be useful as formal embodiments of our understanding of biological systems, computational models must be put into a consistent form that can be communicated more directly between the software tools used to work with them. In this chapter, we describe the Systems Biology Markup Language (SBML), a format for representing models in a way that can be used by different software systems to communicate and exchange those models. By supporting SBML as an input and output format, different software tools can all operate on an identical representation of a model, removing opportunities for errors in translation and assuring a common starting point for analyses and simulations. We also take this opportunity to discuss some of the resources available for working with SBML as well as ongoing efforts in SBML’s continuing evolution.

Published
2006

20. SBMLToolbox: an SBML toolbox for MATLAB users

Author

Keating, Sarah M., Bornstein, Benjamin J., Finney, Andrew, Hucka, Michael, Keating, Sarah M., Bornstein, Benjamin J., Finney, Andrew, and Hucka, Michael

Abstract

We present SBMLToolbox, a toolbox that facilitates importing and exporting models represented in the Systems Biology Markup Language (SBML) in and out of the MATLAB environment and provides functionality that enables an experienced user of either SBML or MATLAB to combine the computing power of MATLAB with the portability and exchangeability of an SBML model. SBMLToolbox supports all levels and versions of SBML.

Published
2006

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