Using machine learning to speed up manual image annotation: Application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Aydin, Zafer ^a   Murray, John I ^a   Waterston, Robert H ^a   Noble, William S ^a,b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b University of Washington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC RECOGNITION; BIOLOGICAL EXPERIMENTS; CELL-CYCLE PROGRESSION; GENERAL METHODOLOGIES; MACHINE LEARNING APPROACHES; MANUAL IMAGE ANNOTATIONS; PROTEIN LOCALIZATION; TIME-LAPSE MICROSCOPY;

CELLS; CYTOLOGY; ERROR CORRECTION; EXPERIMENTS; GENE EXPRESSION; IMAGE ANALYSIS; IMAGE RETRIEVAL; PATTERN RECOGNITION;

SUPPORT VECTOR MACHINES;

CAENORHABDITIS ELEGANS;

CAENORHABDITIS ELEGANS PROTEIN;

ANIMAL; ANIMAL EMBRYO; ARTICLE; ARTIFICIAL INTELLIGENCE; CAENORHABDITIS ELEGANS; COMPUTER ASSISTED DIAGNOSIS; GENE EXPRESSION PROFILING; GENETICS; METABOLISM; METHODOLOGY; PRENATAL DEVELOPMENT; THREE DIMENSIONAL IMAGING;

ANIMALS; ARTIFICIAL INTELLIGENCE; CAENORHABDITIS ELEGANS; CAENORHABDITIS ELEGANS PROTEINS; EMBRYO, NONMAMMALIAN; GENE EXPRESSION PROFILING; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL;

EID: 77949440113     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-84     Document Type: Article

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