Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3)
The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simula...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Bergmann, Frank T. [verfasserIn] Olivier, Brett G. [verfasserIn] Sahle, Sven [verfasserIn] Waltemath, Dagmar - 1981- [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
19.03.2018 |
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| Schlagwörter: |
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| Anmerkung: |
Gesehen am 24.06.2019 |
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| Umfang: |
97 |
| Übergeordnetes Werk: |
Enthalten in: Journal of integrative bioinformatics - Berlin : Walter de Gruyter GmbH, 2004, 15(2018,1) Artikel-Nummer 20170086, 97 Seiten |
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| Übergeordnetes Werk: |
volume:15 ; year:2018 ; number:1 ; extent:97 |
| Links: |
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| DOI / URN: |
10.1515/jib-2017-0086 |
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| Katalog-ID: |
1667838563 |
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10.1515/jib-2017-0086 doi (DE-627)1667838563 (DE-599)KXP1667838563 (OCoLC)1341229295 DE-627 ger DE-627 rda eng Bergmann, Frank T. verfasserin (DE-588)1184911258 (DE-627)166376235X aut Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3) Frank T. Bergmann, Jonathan Cooper, Matthias König, Ion Moraru, David Nickerson, Novère Nicolas Le, Brett G. Olivier, Sven Sahle, Lucian Smith, Dagmar Waltemath 19.03.2018 97 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 24.06.2019 The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment. computational modeling reproducibility Simulation experiment Olivier, Brett G. verfasserin (DE-588)1189099543 (DE-627)1667835815 aut Sahle, Sven verfasserin (DE-588)1099116783 (DE-627)85782452X (DE-576)46921466X aut Waltemath, Dagmar 1981- verfasserin (DE-588)1016855753 (DE-627)671615793 (DE-576)352758791 aut Enthalten in Journal of integrative bioinformatics Berlin : Walter de Gruyter GmbH, 2004 15(2018,1) Artikel-Nummer 20170086, 97 Seiten Online-Ressource (DE-627)388546603 (DE-600)2147212-9 (DE-576)28125124X 1613-4516 nnns volume:15 year:2018 number:1 extent:97 https://doi.org/10.1515/jib-2017-0086 Verlag Resolving-System Volltext https://www.degruyter.com/view/j/jib.2018.15.issue-1/jib-2017-0086/jib-2017-0086.xml Verlag Volltext GBV_USEFLAG_U GBV_ILN_382 SYSFLAG_1 GBV_KXP 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2013 GBV_ILN_2013 ISIL_DE-16-250 AR 15 2018 1 97 15(2018,1) Artikel-Nummer 20170086, 97 Seiten 382 01 4382 3891357168 xv 20-03-21 2013 01 DE-16-250 3489465555 00 --%%-- --%%-- --%%-- --%%-- l01 24-06-19 382 00 4382 00 (DE-627)617791376 Fakultät für Informatik und Elektrotechnik <Rostock> 382 00 4382 20 (DE-627)511037899 Zeitschrift 382 00 4382 21 (DE-627)511033877 Aufsatz 2013 01 DE-16-250 00 s hd2018 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_10 2013 01 DE-16-250 03 s s_97 2013 01 DE-16-250 04 p (DE-627)1663763860 Bergmann, Frank T. 2013 01 DE-16-250 04 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 04 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_1 2013 01 DE-16-250 05 p (DE-627)166784055X Olivier, Brett G. 2013 01 DE-16-250 05 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 05 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 05 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 05 s pos_7 2013 01 DE-16-250 06 p (DE-627)1539213579 Sahle, Sven 2013 01 DE-16-250 06 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 06 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 06 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 06 s pos_8 382 01 4382 99 j2018 |
| spelling |
10.1515/jib-2017-0086 doi (DE-627)1667838563 (DE-599)KXP1667838563 (OCoLC)1341229295 DE-627 ger DE-627 rda eng Bergmann, Frank T. verfasserin (DE-588)1184911258 (DE-627)166376235X aut Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3) Frank T. Bergmann, Jonathan Cooper, Matthias König, Ion Moraru, David Nickerson, Novère Nicolas Le, Brett G. Olivier, Sven Sahle, Lucian Smith, Dagmar Waltemath 19.03.2018 97 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 24.06.2019 The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment. computational modeling reproducibility Simulation experiment Olivier, Brett G. verfasserin (DE-588)1189099543 (DE-627)1667835815 aut Sahle, Sven verfasserin (DE-588)1099116783 (DE-627)85782452X (DE-576)46921466X aut Waltemath, Dagmar 1981- verfasserin (DE-588)1016855753 (DE-627)671615793 (DE-576)352758791 aut Enthalten in Journal of integrative bioinformatics Berlin : Walter de Gruyter GmbH, 2004 15(2018,1) Artikel-Nummer 20170086, 97 Seiten Online-Ressource (DE-627)388546603 (DE-600)2147212-9 (DE-576)28125124X 1613-4516 nnns volume:15 year:2018 number:1 extent:97 https://doi.org/10.1515/jib-2017-0086 Verlag Resolving-System Volltext https://www.degruyter.com/view/j/jib.2018.15.issue-1/jib-2017-0086/jib-2017-0086.xml Verlag Volltext GBV_USEFLAG_U GBV_ILN_382 SYSFLAG_1 GBV_KXP 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2013 GBV_ILN_2013 ISIL_DE-16-250 AR 15 2018 1 97 15(2018,1) Artikel-Nummer 20170086, 97 Seiten 382 01 4382 3891357168 xv 20-03-21 2013 01 DE-16-250 3489465555 00 --%%-- --%%-- --%%-- --%%-- l01 24-06-19 382 00 4382 00 (DE-627)617791376 Fakultät für Informatik und Elektrotechnik <Rostock> 382 00 4382 20 (DE-627)511037899 Zeitschrift 382 00 4382 21 (DE-627)511033877 Aufsatz 2013 01 DE-16-250 00 s hd2018 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_10 2013 01 DE-16-250 03 s s_97 2013 01 DE-16-250 04 p (DE-627)1663763860 Bergmann, Frank T. 2013 01 DE-16-250 04 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 04 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_1 2013 01 DE-16-250 05 p (DE-627)166784055X Olivier, Brett G. 2013 01 DE-16-250 05 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 05 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 05 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 05 s pos_7 2013 01 DE-16-250 06 p (DE-627)1539213579 Sahle, Sven 2013 01 DE-16-250 06 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 06 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 06 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 06 s pos_8 382 01 4382 99 j2018 |
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10.1515/jib-2017-0086 doi (DE-627)1667838563 (DE-599)KXP1667838563 (OCoLC)1341229295 DE-627 ger DE-627 rda eng Bergmann, Frank T. verfasserin (DE-588)1184911258 (DE-627)166376235X aut Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3) Frank T. Bergmann, Jonathan Cooper, Matthias König, Ion Moraru, David Nickerson, Novère Nicolas Le, Brett G. Olivier, Sven Sahle, Lucian Smith, Dagmar Waltemath 19.03.2018 97 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gesehen am 24.06.2019 The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment. computational modeling reproducibility Simulation experiment Olivier, Brett G. verfasserin (DE-588)1189099543 (DE-627)1667835815 aut Sahle, Sven verfasserin (DE-588)1099116783 (DE-627)85782452X (DE-576)46921466X aut Waltemath, Dagmar 1981- verfasserin (DE-588)1016855753 (DE-627)671615793 (DE-576)352758791 aut Enthalten in Journal of integrative bioinformatics Berlin : Walter de Gruyter GmbH, 2004 15(2018,1) Artikel-Nummer 20170086, 97 Seiten Online-Ressource (DE-627)388546603 (DE-600)2147212-9 (DE-576)28125124X 1613-4516 nnns volume:15 year:2018 number:1 extent:97 https://doi.org/10.1515/jib-2017-0086 Verlag Resolving-System Volltext https://www.degruyter.com/view/j/jib.2018.15.issue-1/jib-2017-0086/jib-2017-0086.xml Verlag Volltext GBV_USEFLAG_U GBV_ILN_382 SYSFLAG_1 GBV_KXP 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2013 GBV_ILN_2013 ISIL_DE-16-250 AR 15 2018 1 97 15(2018,1) Artikel-Nummer 20170086, 97 Seiten 382 01 4382 3891357168 xv 20-03-21 2013 01 DE-16-250 3489465555 00 --%%-- --%%-- --%%-- --%%-- l01 24-06-19 382 00 4382 00 (DE-627)617791376 Fakultät für Informatik und Elektrotechnik <Rostock> 382 00 4382 20 (DE-627)511037899 Zeitschrift 382 00 4382 21 (DE-627)511033877 Aufsatz 2013 01 DE-16-250 00 s hd2018 2013 01 DE-16-250 01 s (DE-627)1410508463 wissenschaftlicher Artikel (Zeitschrift) 2013 01 DE-16-250 02 s per_10 2013 01 DE-16-250 03 s s_97 2013 01 DE-16-250 04 p (DE-627)1663763860 Bergmann, Frank T. 2013 01 DE-16-250 04 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 04 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 04 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 04 s pos_1 2013 01 DE-16-250 05 p (DE-627)166784055X Olivier, Brett G. 2013 01 DE-16-250 05 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 05 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 05 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 05 s pos_7 2013 01 DE-16-250 06 p (DE-627)1539213579 Sahle, Sven 2013 01 DE-16-250 06 k (DE-627)1416734031 BIOQUANT 2013 01 DE-16-250 06 k (DE-627)1416737987 Centre for Organismal Studies Heidelberg (COS) 2013 01 DE-16-250 06 s (DE-627)1410501914 Verfasser 2013 01 DE-16-250 06 s pos_8 382 01 4382 99 j2018 |
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Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3) Frank T. Bergmann, Jonathan Cooper, Matthias König, Ion Moraru, David Nickerson, Novère Nicolas Le, Brett G. Olivier, Sven Sahle, Lucian Smith, Dagmar Waltemath |
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Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 3 (L1V3) |
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The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment. Gesehen am 24.06.2019 |
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The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment. Gesehen am 24.06.2019 |
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The creation of computational simulation experiments to inform modern biological research poses challenges to reproduce, annotate, archive, and share such experiments. Efforts such as SBML or CellML standardize the formal representation of computational models in various areas of biology. The Simulation Experiment Description Markup Language (SED-ML) describes what procedures the models are subjected to, and the details of those procedures. These standards, together with further COMBINE standards, describe models sufficiently well for the reproduction of simulation studies among users and software tools. The Simulation Experiment Description Markup Language (SED-ML) is an XML-based format that encodes, for a given simulation experiment, (i) which models to use; (ii) which modifications to apply to models before simulation; (iii) which simulation procedures to run on each model; (iv) how to post-process the data; and (v) how these results should be plotted and reported. SED-ML Level 1 Version 1 (L1V1) implemented support for the encoding of basic time course simulations. SED-ML L1V2 added support for more complex types of simulations, specifically repeated tasks and chained simulation procedures. SED-ML L1V3 extends L1V2 by means to describe which datasets and subsets thereof to use within a simulation experiment. Gesehen am 24.06.2019 |
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