ArticleBiophysical journal2011
Are assumptions about the model type necessary in reaction-diffusion modeling? A FRAP application.
Article in Biophysical journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Exploring focal adhesion data: dynamic parameter extraction from FRAP and FLAP experiments using chemical master equation.Frontiers in molecular biosciences · 2025Article
- OptoGap is an optogenetics-enabled assay for quantification of cell-cell coupling in multicellular cardiac tissue.Scientific reports · 2021Article
- Pilot study of global endocrine disrupting activity in Iowa public drinking water utilities using cell-based assays.The Science of the total environment · 2020Article
- Quantitative diffusion measurements using the open-source software PyFRAP.Nature communications · 2018Article
- Improving Parameter Inference from FRAP Data: an Analysis Motivated by Pattern Formation in the Drosophila Wing Disc.Bulletin of mathematical biology · 2017Article
- Article
- Parameter importance in FRAP acquisition and analysis: a simulation approach.Biophysical journal · 2013Article
- Dissection of cell cycle-dependent dynamics of Dnmt1 by FRAP and diffusion-coupled modeling.Nucleic acids research · 2013Article
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8 authors.
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Abstract
At present, fluorescence recovery after photobleaching (FRAP) data are interpreted using various types of reaction-diffusion (RD) models: the model type is usually fixed first, and corresponding model parameters are inferred subsequently. In this article, we describe what we believe to be a novel approach for RD modeling without using any assumptions of model type or parameters. To the best of our knowledge, this is the first attempt to address both model-type and parameter uncertainties in inverting FRAP data. We start from the most general RD model, which accounts for a flexible number of molecular fractions, all mobile, with different diffusion coefficients. The maximal number of possible binding partners is identified and optimal parameter sets for these models are determined in a global search of the parameter-space using the Simulated Annealing strategy. The numerical performance of the described techniques was assessed using artificial and experimental FRAP data. Our general RD model outperformed the standard RD models used previously in modeling FRAP measurements and showed that intracellular molecular mobility can only be described adequately by allowing for multiple RD processes. Therefore, it is important to search not only for the optimal parameter set but also for the optimal model type.
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