DocumentCode :
3299648
Title :
An image informatics method for automated quantitative analysis of phenotype visual similarities
Author :
Shamir, Lior ; Eckley, D. Mark ; Delaney, John ; Orlov, Nikita ; Goldberg, Ilya G.
Author_Institution :
Lab. of Genetics, NIH, Baltimore, MD
fYear :
2009
fDate :
9-10 April 2009
Firstpage :
96
Lastpage :
99
Abstract :
The post genomic era introduced the need to define single gene functions within biological pathways. A systems biology approach can be realized by automating image acquisition and phenotype classification. While machinery for automated data acquisition have been developing rapidly in the past years, the main bottleneck remains the effectiveness of the computer vision algorithms. Here we describe a fully automated process for finding phenotype similarities within a dataset acquired from an RNAi screen. The source code for the algorithms is available for free download.
Keywords :
bioinformatics; computer vision; genetics; image classification; medical image processing; organic compounds; RNAi screen; automated quantitative analysis; computer vision; image acquisition; image informatics method; phenotype classification; phenotype visual similarities; post genomic era; single gene functions; systems biology; Availability; Bioinformatics; Computer vision; Data mining; Feature extraction; Genomics; Image analysis; Informatics; Polynomials; Tiles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Life Science Systems and Applications Workshop, 2009. LiSSA 2009. IEEE/NIH
Conference_Location :
Bethesda, MD
Print_ISBN :
978-1-4244-4292-8
Electronic_ISBN :
978-1-4244-4293-5
Type :
conf
DOI :
10.1109/LISSA.2009.4906718
Filename :
4906718
Link To Document :
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