title: A Parts Database with Consensus Parameter Estimation for Synthetic Circuit Design.
abstract: Mathematical modeling and numerical simulation are crucial to support design decisions in synthetic biology. Accurate estimation of parameter values is key, as direct experimental measurements are difficult and time-consuming. Insufficient data, incompatible measurements, and specialized models that lack universal parameters make this task challenging. Here, we have created a database (PAMDB) that integrates data from 135 publications that contain 118 circuits and 165 genetic parts of the bacterium Escherichia coli. We used a succinct, universal model formulation to describe the part behavior in each circuit. We introduce a constrained consensus inference method that was used to infer the value of the model parameters and evaluated its performance through cross-validation in a benchmark of 23 circuits. We discuss these results and summarize the challenges in data integration and parameter inference. This work provides a resource and a methodology that can be used as a point of reference for synthetic circuit modeling.
authors.affiliation: Department of Computer Science & UC Davis Genome Center, University of California Davis , Davis, California 95616 United States.
authors.forename: Linh
authors.initials: L
authors.lastname: Huynh
authors.affiliation: Department of Computer Science & UC Davis Genome Center, University of California Davis , Davis, California 95616 United States.
authors.forename: Ilias
authors.initials: I
authors.lastname: Tagkopoulos
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D016208:Databases, Factual; D004926:Escherichia coli / Q000235:genetics; D053263:Gene Regulatory Networks; D008962:Models, Theoretical; D058615:Synthetic Biology / Q000379:methods*
keywords: data integration; gene circuit; mathematical model; parameter estimation; parameter inference