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Journal article

Efficiently and Effectively Recognizing Toricity of Steady State Varieties

Abstract:
Recently, symbolic computation and computer algebra systems have beensuccessfully applied in systems biology, especially in chemical reactionnetwork theory. One advantage of symbolic computation is its potential forqualitative answers to biological questions. Qualitative methods analyzedynamical input systems as formal objects, in contrast to investigating onlypart of the state space, as is the case with numerical simulation. However,symbolic computation tools and libraries have a different set of requirementsfor their input data than their numerical counterparts. A common format used inmathematical modeling of biological processes is SBML. We illustrate that theuse of SBML data in symbolic computation requires significant pre-processing,incorporating external biological and mathematical expertise. ODEbase provideshigh quality symbolic computation input data derived from established existingbiomodels, covering in particular the BioModels database.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s11786-020-00479-9

Authors

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Role:
Author
ORCID:
0000-0001-6361-4331
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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0001-5789-2976
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Role:
Author
ORCID:
0000-0001-5698-3542
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Role:
Author
ORCID:
0000-0001-5322-5068


Publisher:
Springer
Journal:
Mathematics in Computer Science More from this journal
Volume:
15
Issue:
2
Pages:
199-232
Publication date:
2020-07-21
DOI:
EISSN:
1661-8289
ISSN:
1661-8270


Language:
English
Pubs id:
1124542
Local pid:
pubs:1124542
Source identifiers:
W2980220245
Deposit date:
2025-12-24
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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