Summary of the DREAM8 Parameter Estimation Challenge

Toward Parameter Identification for Whole-Cell Models

DREAM8 Parameter Estimation Challenge Consortium, Hao Tang

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Original languageEnglish (US)
Article numbere1004096
JournalPLoS Computational Biology
Volume11
Issue number5
DOIs
StatePublished - May 1 2015

Fingerprint

Parameter Identification
Parameter estimation
Parameter Estimation
Identification (control systems)
Cell
cells
Model
Reverse engineering
Cloud computing
Model structures
parameter estimation
parameter
Reverse Engineering
Identifiability
Computer Simulation
Estimation Algorithms
Genotype
Cloud Computing
Phenotype
Bacteria

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Modeling and Simulation
  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Molecular Biology
  • Ecology
  • Cellular and Molecular Neuroscience

Cite this

Summary of the DREAM8 Parameter Estimation Challenge : Toward Parameter Identification for Whole-Cell Models. / DREAM8 Parameter Estimation Challenge Consortium; Tang, Hao.

In: PLoS Computational Biology, Vol. 11, No. 5, e1004096, 01.05.2015.

Research output: Contribution to journalArticle

DREAM8 Parameter Estimation Challenge Consortium ; Tang, Hao. / Summary of the DREAM8 Parameter Estimation Challenge : Toward Parameter Identification for Whole-Cell Models. In: PLoS Computational Biology. 2015 ; Vol. 11, No. 5.
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