TY  - JOUR
A1  - Conrad, Christian
A1  - Erfle, Holger
A1  - Warnat, Patrick
A1  - Daigle, Nathalie
A1  - Lörch, Thomas
A1  - Ellenberg, Jan
A1  - Pepperkok, Rainer
A1  - Eils, Roland
T1  - Automatic Identification of Subcellular Phenotypes on Human Cell Arrays
Y1  - 2004/06/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1130 
EP  - 1136 
DO  - 10.1101/gr.2383804 
VL  - 14 
IS  - 6 
UR  - http://genome.cshlp.org/content/14/6/1130.abstract 
N2  - Light microscopic analysis of cell morphology provides a high-content readout of cell function and protein localization. Cell arrays and microwell transfection assays on cultured cells have made cell phenotype analysis accessible to high-throughput experiments. Both the localization of each protein in the proteome and the effect of RNAi knock-down of individual genes on cell morphology can be assayed by manual inspection of microscopic images. However, the use of morphological readouts for functional genomics requires fast and automatic identification of complex cellular phenotypes. Here, we present a fully automated platform for high-throughput cell phenotype screening combining human live cell arrays, screening microscopy, and machine-learning-based classification methods. Efficiency of this platform is demonstrated by classification of eleven subcellular patterns marked by GFP-tagged proteins. Our classification method can be adapted to virtually any microscopic assay based on cell morphology, opening a wide range of applications including large-scale RNAi screening in human cells. 
ER  -