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Flowmax: A Computational Lymphocyte Phenotyping Tool For Deriving Cell Biological Insights From CFSE Flow Cytometry Time Courses (2012-234)


详细技术说明

A researcher from UC San Diego has developed an improved methodology and a corresponding graphical computational tool for analysis of cell proliferation time courses to reduce misinterpretation.  This integrated modeling and analysis tool fits mathematical models to measured flow cytometry dye dilution experiments to model cellular biological processes (e.g. propensity of cells to respond, interdivision time, survival time) that describe the measured population dynamics. The computational tool consists of three main parts. First, it offers a graphical user friendly environment for basic analysis of flow cytometry data, which allows users to construct fluorescence histograms of viable cells for multiple experimental time points.Second, the tool trains two computational models on the experimental data using an optimized non-linear approach. The first model is used as an adaptor to facilitate optimal fitting of a second cell population model. The second step is repeated numerous times and each solution is subjected to parameter sensitivity analysis as part of a final confidence estimation step.A clustering approach is then used to derive the minimal set of unique solutions and the parameter confidence. Furthermore, numerous solution analysis tools were integrated to help analyze the statistical significance of solutions, as well as to visualize and deconstruct all solutions in terms of cellular and population phenotypes. In summary, this novel approach integrates modeling and analysis and allows for the estimation of parameter sensitivity and uniqueness, enabling useful solution comparisons. The tool has been used to discern novel immunological signaling phenotypes in a laboratory setting and can be directly applied to facilitate improved immunological and cancer screening in clinics.


其他

Intellectual Property Info

This patent-pending technology and software is available for commercial development.


Related Materials

Shokhirev MN, Hoffmann A. FlowMax: A Computational Tool for Maximum Likelihood Deconvolution of CFSE Time Courses. PLoS One. 2013 Jun 27;8(6):e6762


Tech ID/UC Case

25024/2012-841-0


Related Cases

2012-841-0


国家/地区

美国

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