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Refinement-Based Modeling of the ErbB Signaling Pathway

Bogdan Iancu, Usman Sanwal, Cristian Gratie, Ion Petre, Refinement-Based Modeling of the ErbB Signaling Pathway. Computers in Biology and Medicine 106, 91–96, 2019.

http://dx.doi.org/10.1016/j.compbiomed.2019.01.016

Abstract:

The construction of large scale biological models is a laborious task, which is often addressed by adoptingiterative routines for model augmentation, adding certain details to an initial high level abstraction of thebiological phenomenon of interest. Refitting a model at every step of its development is time consuming andcomputationally intensive. The concept ofmodel refinementbrings about an effective alternative by providingadequate parameter values that ensure the preservation of its quantitativefit at every refinement step. Wedemonstrate this approach by constructing the largest-ever refinement-based biomodel, consisting of 421 speciesand 928 reactions. We start from an alreadyfit, relatively small literature model whose consistency we checkformally. We then construct the final model through an algorithmic step-by-step refinement procedure that ensures the preservation of the model'sfit.

BibTeX entry:

@ARTICLE{jIaSaGrPe19a,
  title = {Refinement-Based Modeling of the ErbB Signaling Pathway},
  author = {Iancu, Bogdan and Sanwal, Usman and Gratie, Cristian and Petre, Ion},
  journal = {Computers in Biology and Medicine},
  volume = {106},
  publisher = {Elsevier},
  pages = {91–96},
  year = {2019},
  ISSN = {0010-4825},
}

Belongs to TUCS Research Unit(s): Computational Biomodeling Laboratory (Combio Lab)

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