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BMCBI
2004
176views more  BMCBI 2004»
13 years 4 months ago
Boosting accuracy of automated classification of fluorescence microscope images for location proteomics
Background: Detailed knowledge of the subcellular location of each expressed protein is critical to a full understanding of its function. Fluorescence microscopy, in combination w...
Kai Huang, Robert F. Murphy
ISBI
2002
IEEE
14 years 5 months ago
Automated determination of protein subcellular locations from 3D fluorescence microscope images
Knowing the subcellular location of a protein is critical to a full understanding of its function, and automated, objective methods for assigning locations are needed as part of t...
Meel Velliste, Robert F. Murphy
ISBI
2004
IEEE
14 years 5 months ago
Automated Classification of Subcellular Patterns In Multicell Images Without Segmentation Into Single Cells
Fluorescence microscope images capture information from an entire field of view, which often comprises several cells scattered on the slide. We have previously trained classifiers...
Kai Huang, Robert F. Murphy
KDD
2003
ACM
142views Data Mining» more  KDD 2003»
14 years 4 months ago
Extracting information from text and images for location proteomics
There is extensive interest in automating the collection, organization and summarization of biological data. Data in the form of figures and accompanying captions in literature pr...
Zhenzhen Kou, William W. Cohen, Robert F. Murphy
BMCBI
2006
118views more  BMCBI 2006»
13 years 4 months ago
A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images
Background: Knowledge of the subcellular location of a protein is critical to understanding how that protein works in a cell. This location is frequently determined by the interpr...
Shann-Ching Chen, Robert F. Murphy