A multiresolution approach to automated classification of protein subcellular location images

BMC Bioinformatics

Volumn 8, Issue , 2007, Pages

  Chebira, Amina ^a   Barbotin, Yann ^a,c   Jackson, Charles ^a   Merryman, Thomas ^a   Srinivasa, Gowri ^a   Murphy, Robert F ^a,b   Kovačević, Jelena ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c EPFL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

COMBINATION OF CLASSIFIERS; HARALICK TEXTURE FEATURES; MACHINE LEARNING METHODS; MULTI-RESOLUTION APPROACH; MULTI-RESOLUTION SUBSPACE; NEURAL NETWORK CLASSIFIER; PROTEIN SUBCELLULAR LOCATION; SUBCELLULAR LOCATION OF PROTEINS;

FLUORESCENCE MICROSCOPY; LEARNING SYSTEMS; TEXTURES;

PROTEINS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; BIOINFORMATICS; CELLULAR DISTRIBUTION; CLASSIFICATION ALGORITHM; CLASSIFIER; CONTROLLED STUDY; HELA CELL; HUMAN; HUMAN CELL; MOLECULAR IMAGING; OPTICAL RESOLUTION; PROTEIN LOCALIZATION; CELL FRACTIONATION; COMPUTER ASSISTED DIAGNOSIS; FLUORESCENCE MICROSCOPY; IMAGE ENHANCEMENT; METABOLISM; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; ULTRASTRUCTURE;

PROTEIN;

IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY, FLUORESCENCE; PROTEINS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBCELLULAR FRACTIONS;

EID: 34547650901     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-8-210     Document Type: Article

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