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Bioinformatics

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Image processing

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Time Series Data For 3b Image Processing, George Mcnamara Jan 2014

Time Series Data For 3b Image Processing, George Mcnamara

George McNamara

Time series data for 3B image processing

Four time series data sets of Stellaris single molecules RNA FISH (fluorescence in situ hybridization). All four datasets are 301 imaqe planes. FISH probes are to TOP1 mRNA (Topoisomerase I)in Saos osterosarcoma cells.

One dataset is 10 millisecond exposures (very dim), acquired in Streaming acquisition mode (no hardware overhead).

The other three datasets are a three consecutive planes of the same XY field of view.

I have included image processing results for:

PiMP - a fast method developed by Sebastian Munck et al 2012, http://www.ncbi.nlm.nih.gov/pubmed/?term=22357945

and greatly improved performance by Glen Macdonald (Seattle). …


Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes Jan 2010

Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes

Jeffrey S. Morris

Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the …