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TitleArchitectuurstjilen voor HCS Data Verwerking
Author(s)Wim Robijn
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AbstractDigital cameras and computer controlled microscopes led to automation in the drug discovery cycle. High Content Screening is a method that uses the digital cameras and microscopes to search for good drug candidates. It produces enormous amounts of data. This data needs to be processed efficiently to find the best drug candidate. The fast evolving market places two other restrictions on a good HCS processing program: reusability and maintainability. This thesis will look at three different architectural styles that can be used to design a HCS data processing program. To compare the three suggested architectural styles, the Goal-Question-Metric approach is used. The results indicate that a data-centered architectural style is the best for a HCS data processing program. The data flow architectural style is the best for a HCS data processing program. The dta flow architectural style is poor on performance, because of constraints from the pharmaceutical industry. A mix between these two architectural styles decreases the advantages of the data flow style.
BibTeX
@mastersthesis{Robijn2007,
	author = {Wim Robijn},
	title = {Architectuurstjilen voor HCS Data Verwerking},
	month = {July},
	school = {Universiteit Antwerpen},
	year = {2007},
	note = {Thesis in samenwerking met DCILabs (http://www.dcilabs.com)}
}
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 Lab On REengineering - Antwerpen, last modified 12:35:26 17 August 2010