Toward predictive modeling of large and complex biological signaling networks

Rachel A. Hillmer, Fumiaki Katagiri

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


The main goal of this article is to identify critical issues that arise when building in silico models that can predict the behavior of complex biological signaling networks. We discuss practical approaches to overcome, circumvent, or moderate these issues. Here we focus on modeling spatially homogenous systems, such as those consisting of cells of the same type receiving the same input. Proper modeling of spatially heterogeneous systems requires additional model features and added modeling scales, beyond those required for spatially homogenous systems. These different modeling scales are defined here as different layers in the hierarchical relationships in a network. For example, protein molecules and cells that contain the protein molecules belong to different scales.

Original languageEnglish (US)
Pages (from-to)77-83
Number of pages7
JournalPhysiological and Molecular Plant Pathology
StatePublished - Jul 1 2016

Bibliographical note

Funding Information:
We thank Yungil Kim for valuable discussion in preparing this perspective. The relevant work in F. K.’s laboratory was partly supported by grants from the National Science Foundation , MCB-0918908 and IOS-1121425 . R. A. H. was supported by a Doctoral Dissertation Fellowship and a Plant Biological Sciences Summer Fellowship from University of Minnesota .


  • Network reconstitution
  • Signaling allocation

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