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  ODEbase: A Repository of ODE Systems for Systems Biology

Lüders, C., Sturm, T., & Radulescu, O. (2022). ODEbase: A Repository of ODE Systems for Systems Biology. Retrieved from https://arxiv.org/abs/2201.08980.

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arXiv:2201.08980.pdf (Preprint), 374KB
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 Urheber:
Lüders, Christoph1, Autor
Sturm, Thomas2, Autor                 
Radulescu, Ovidiu1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2Automation of Logic, MPI for Informatics, Max Planck Society, ou_1116545              

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Schlagwörter: Quantitative Biology, Molecular Networks, q-bio.MN,Computer Science, Symbolic Computation, cs.SC
 Zusammenfassung: Recently, symbolic computation and computer algebra systems have been
successfully applied in systems biology, especially in chemical reaction
network theory. One advantage of symbolic computation is its potential for
qualitative answers to biological questions. Qualitative methods analyze
dynamical input systems as formal objects, in contrast to investigating only
part of the state space, as is the case with numerical simulation. However,
symbolic computation tools and libraries have a different set of requirements
for their input data than their numerical counterparts. A common format used in
mathematical modeling of biological processes is SBML. We illustrate that the
use of SBML data in symbolic computation requires significant pre-processing,
incorporating external biological and mathematical expertise. ODEbase provides
high quality symbolic computation input data derived from established existing
biomodels, covering in particular the BioModels database.

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Sprache(n): eng - English
 Datum: 2022-01-222022
 Publikationsstatus: Online veröffentlicht
 Seiten: 8 p.
 Ort, Verlag, Ausgabe: -
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 Identifikatoren: arXiv: 2201.08980
URI: https://arxiv.org/abs/2201.08980
BibTex Citekey: Lueders2201.08980
 Art des Abschluß: -

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