DocumentCode :
2720433
Title :
A graphical model to determine the subcellular protein location in artificial tissues
Author :
Glory-Afshar, Estelle ; Osuna-Highley, Elvira ; Granger, Brian ; Murphy, Robert F.
Author_Institution :
Dept. of Biomed. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2010
fDate :
14-17 April 2010
Firstpage :
1037
Lastpage :
1040
Abstract :
Location proteomics is concerned with the systematic analysis of the subcellular location of proteins. In order to perform comprehensive analysis of all protein location patterns, automated methods are needed. With the goal of extending automated subcellular location pattern analysis methods to high resolution images of tissues, 3D confocal microscope images of polarized CaCo2 cells immunostained for various proteins were collected. A three-color staining protocol was developed that permits parallel imaging of proteins of interest as well as DNA and the actin cytoskeleton. The collection is composed of 11 to 21 images for each of the 9 proteins that depict major subcellular patterns. A classifier was trained to recognize the subcellular location pattern of segmented cells with an accuracy of 89.2%. Using the Prior Updating method allowed improvement of this accuracy to 99.6%. This study demonstrates the benefit of using a graphical model approach for improving the pattern classification in tissue images.
Keywords :
DNA; biological tissues; biomedical optical imaging; cancer; cellular biophysics; feature extraction; fluorescence; image classification; image resolution; image segmentation; learning (artificial intelligence); medical image processing; optical microscopy; proteins; proteomics; 3D confocal microscope image; DNA; actin cytoskeleton; artificial tissue; graphical model; location proteomics; machine learning; parallel protein imaging; pattern classification; polarized CaCo2 cell; segmented cells; subcellular location pattern; subcellular protein location; three-color staining protocol; Graphical models; High-resolution imaging; Image resolution; Microscopy; Pattern analysis; Performance analysis; Polarization; Proteins; Proteomics; Protocols; artificial tissue; graphical model; machine learning; prior updating; subcellular protein location;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
ISSN :
1945-7928
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2010.5490167
Filename :
5490167
Link To Document :
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