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Automated Classification of Images from Crystallisation Experiments

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Title of host publicationAdvances in Data Mining: Applications in Medicine, Web Mining, Marketing, Image and Signal Mining
DatePublished - 1 Feb 2006
Pages459-473
Number of pages15
PublisherSpringer Berlin / Heidelberg
Volume4065
Edition2006
Original languageEnglish
ISBN (Print)978-3-540-36036-0

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume4065

Abstract

Protein crystallography can often provide the three-dimensional structures of macro-molecules necessary for functional studies and drug design. However, identifying the conditions that will provide diffraction quality crystals often requires numerous experiments. The use of robots has led to a dramatic increase in the number of crystallisation experiments performed in most laboratories and, in structural genomics centres, tens of thousands of experiments can be produced daily. The results of these experiments must be assessed repeatedly over time and inspection of the results by eye is becoming increasingly impractical. A number of systems are now available for automated imaging of crystallisation experiments and the primary aim of this research is the development of software to automate image analysis.

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