Hypothesis testing via integrated computer modeling and digital fluorescence microscopy

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Computational modeling has the potential to add an entirely new approach to hypothesis testing in yeast cell biology. Here, we present a method for seamless integration of computational modeling with quantitative digital fluorescence microscopy. This integration is accomplished by developing computational models based on hypotheses for underlying cellular processes that may give rise to experimentally observed fluorescent protein localization patterns. Simulated fluorescence images are generated from the computational models of underlying cellular processes via a "model-convolution" process. These simulated images can then be directly compared to experimental fluorescence images in order to test the model. This method provides a framework for rigorous hypothesis testing in yeast cell biology via integrated mathematical modeling and digital fluorescence microscopy.

Original languageEnglish (US)
Pages (from-to)232-237
Number of pages6
JournalMethods
Volume41
Issue number2
DOIs
StatePublished - Feb 1 2007

Fingerprint

Fluorescence microscopy
Fluorescence Microscopy
Cell Biology
Yeasts
Fluorescence
Cytology
Testing
Yeast
Convolution
Proteins

Keywords

  • Model-convolution
  • Modeling
  • Simulation
  • Stochastic
  • Yeast

Cite this

Hypothesis testing via integrated computer modeling and digital fluorescence microscopy. / Gardner, Melissa K; Odde, David J; Bloom, Kerry.

In: Methods, Vol. 41, No. 2, 01.02.2007, p. 232-237.

Research output: Contribution to journalArticle

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