View in EDS

Implementing biological hybrid systems: Allowing composition and avoiding stiffness.

Saved in:
Bibliographic Details
Title: Implementing biological hybrid systems: Allowing composition and avoiding stiffness.
Authors: Assar, Rodrigo1,2 rodrigo.assar@gmail.com, Sherman, David J.3 david.sherman@inria.fr
Source: Applied Mathematics & Computation. Oct2013, Vol. 223, p167-179. 13p.
Subjects: Hybrid systems, Stiffness (Mechanics), Numerical solutions to differential equations, Number theory, Mathematical models, Numerical analysis
Abstract: Abstract: The theory of hybrid systems allows us to model biological functions with many interactive processes, describe complexity and hierarchy levels, and consider behavior law changes. However, we need to develop an implementation to simulate these models. The BioRica framework allows a non-ambiguous implementation, and, as shown here, the QSS method (Quantized States Systems) helps us to approach complex systems in a more efficient way. This method allows us to numerically solve stiff differential equations by separately choosing the temporal partition for each sub-model and variable, depending on how fast it changes over time. With that, one obtains more accurate solutions and decreases the number of computations compared to classic methods. Moreover, QSS does not need to store trajectories and interpolate when mode transitions occur between partition times. Herein, we exhibit a translation from BioRica to QSS models, which preserves the semantics. We implement QSS method with BioRica, and illustrate with applications in Biology, the Tyson model of cell cycle, and examples in Engineering. [Copyright &y& Elsevier]
Copyright of Applied Mathematics & Computation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 92873156
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Implementing biological hybrid systems: Allowing composition and avoiding stiffness.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Assar%2C+Rodrigo%22">Assar, Rodrigo</searchLink><relatesTo>1,2</relatesTo><i> rodrigo.assar@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Sherman%2C+David+J%2E%22">Sherman, David J.</searchLink><relatesTo>3</relatesTo><i> david.sherman@inria.fr</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Applied+Mathematics+%26+Computation%22">Applied Mathematics & Computation</searchLink>. Oct2013, Vol. 223, p167-179. 13p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Hybrid+systems%22">Hybrid systems</searchLink><br /><searchLink fieldCode="DE" term="%22Stiffness+%28Mechanics%29%22">Stiffness (Mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Numerical+solutions+to+differential+equations%22">Numerical solutions to differential equations</searchLink><br /><searchLink fieldCode="DE" term="%22Number+theory%22">Number theory</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Numerical+analysis%22">Numerical analysis</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Abstract: The theory of hybrid systems allows us to model biological functions with many interactive processes, describe complexity and hierarchy levels, and consider behavior law changes. However, we need to develop an implementation to simulate these models. The BioRica framework allows a non-ambiguous implementation, and, as shown here, the QSS method (Quantized States Systems) helps us to approach complex systems in a more efficient way. This method allows us to numerically solve stiff differential equations by separately choosing the temporal partition for each sub-model and variable, depending on how fast it changes over time. With that, one obtains more accurate solutions and decreases the number of computations compared to classic methods. Moreover, QSS does not need to store trajectories and interpolate when mode transitions occur between partition times. Herein, we exhibit a translation from BioRica to QSS models, which preserves the semantics. We implement QSS method with BioRica, and illustrate with applications in Biology, the Tyson model of cell cycle, and examples in Engineering. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Mathematics & Computation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=92873156
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.amc.2013.08.012
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 167
    Subjects:
      – SubjectFull: Hybrid systems
        Type: general
      – SubjectFull: Stiffness (Mechanics)
        Type: general
      – SubjectFull: Numerical solutions to differential equations
        Type: general
      – SubjectFull: Number theory
        Type: general
      – SubjectFull: Mathematical models
        Type: general
      – SubjectFull: Numerical analysis
        Type: general
    Titles:
      – TitleFull: Implementing biological hybrid systems: Allowing composition and avoiding stiffness.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Assar, Rodrigo
      – PersonEntity:
          Name:
            NameFull: Sherman, David J.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 10
              Text: Oct2013
              Type: published
              Y: 2013
          Identifiers:
            – Type: issn-print
              Value: 00963003
          Numbering:
            – Type: volume
              Value: 223
          Titles:
            – TitleFull: Applied Mathematics & Computation
              Type: main
ResultId 1