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Quantitative Modeling of Integrase Dynamics Using a Novel Python Toolbox for Parameter Inference in Synthetic Biology

Swaminathan, Anandh and Hsiao, Victoria and Murray, Richard M. (2017) Quantitative Modeling of Integrase Dynamics Using a Novel Python Toolbox for Parameter Inference in Synthetic Biology. . (Submitted) http://resolver.caltech.edu/CaltechAUTHORS:20170705-101737121

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Abstract

The recent abundance of high-throughput data for biological circuits enables data-driven quantitative modeling and parameter estimation. Common modeling issues include long computational times during parameter estimation, and the need for many iterations of this cycle to match data. Here, we present BioSCRAPE (Bio-circuit Stochastic Single-cell Reaction Analysis and Parameter Estimation) - a Python package for fast and flexible modeling and simulation for biological circuits. The BioSCRAPE package can be used for deterministic or stochastic simulations and can incorporate delayed reactions, cell growth, and cell division. Simulation run times obtained with the package are comparable to those obtained using C code - this is particularly advantageous for computationally expensive applications such as Bayesian inference or simulation of cell lineages. We first show the package's simulation capabilities on a variety of example simulations of stochastic gene expression. We then further demonstrate the package by using it to do parameter inference for a model of integrase dynamics using experimental data. The BioSCRAPE package is publicly available online along with more detailed documentation and examples.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/121152 DOIDiscussion Paper
http://www.biorxiv.org/content/early/2017/03/27/121152OrganizationDiscussion Paper
ORCID:
AuthorORCID
Hsiao, Victoria0000-0001-9297-1522
Murray, Richard M.0000-0002-5785-7481
Additional Information:The copyright holder for this preprint is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license. bioRxiv preprint first posted online Mar. 27, 2017. The authors would like to acknowledge Marcella M. Gomez, Noah Olsman, Vipul Singhal, and Eduardo Sontag for helpful discussions and testing of the software. AS is supported by AFOSR grant FA9550-14-1-0060. The project depicted is sponsored by the Defense Advanced Research Projects Agency (Agreement HR0011-17-2-0008). The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. Author Contributions: AS conceived of BioSCRAPE, wrote the software, developed the examples and code for modeling integrase dynamics, and wrote the technical report with feedback from RMM and VH. VH conceived of performing integrase characterization in TX-TL and collected the experimental data. VH also provided feedback on data analysis, parameter estimation, and the technical report. RMM provided project supervision and feedback on the technical report.
Funders:
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)FA9550-14-1-0060
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008
Record Number:CaltechAUTHORS:20170705-101737121
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170705-101737121
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:78759
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:06 Jul 2017 21:44
Last Modified:06 Jul 2017 21:44

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