Boosting accuracy of automated classification of fluorescence microscope images for location proteomics
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The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging.Toward a confocal subcellular atlas of the human proteomeObjective clustering of proteins based on subcellular location patternsPredicting Neuroinflammation in Morphine Tolerance for Tolerance Therapy from Immunostaining Images of Rat Spinal CordAutonomous screening of C. elegans identifies genes implicated in synaptogenesisA machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classificationObject type recognition for automated analysis of protein subcellular location.A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images.Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics.A multiresolution approach to automated classification of protein subcellular location images.Random subwindows and extremely randomized trees for image classification in cell biology.An incremental approach to automated protein localisation.Automatic analysis of dividing cells in live cell movies to detect mitotic delays and correlate phenotypes in time.Chemical address tags of fluorescent bioimaging probesAutomated analysis of protein subcellular location in time series images.Image-derived, three-dimensional generative models of cellular organizationPhenotype recognition with combined features and random subspace classifier ensemble.A spectral graph theoretic approach to quantification and calibration of collective morphological differences in cell images.Classification and clustering analysis of pyruvate dehydrogenase enzyme based on their physicochemical properties.Ranking of multidimensional drug profiling data by fractional-adjusted bi-partitional scores.Detection and classification of thyroid follicular lesions based on nuclear structure from histopathology images.Determining the subcellular location of new proteins from microscope images using local featuresIdentification of cichlid fishes from Lake Malawi using computer vision.A comparative study of cell classifiers for image-based high-throughput screening.The potential of high-content high-throughput microscopy in drug discovery.HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screeningPatient-centered yes/no prognosis using learning machinesA picture is worth a thousand words: genomics to phenomics in the yeast Saccharomyces cerevisiae.Analyzing and mining automated imaging experiments.An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.Large-scale automated analysis of location patterns in randomly tagged 3T3 cells.Specification of spatial relationships in directed graphs of cell signaling networks.Assessing the efficacy of low-level image content descriptors for computer-based fluorescence microscopy image analysis.
P2860
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P2860
Boosting accuracy of automated classification of fluorescence microscope images for location proteomics
description
2004 nî lūn-bûn
@nan
2004 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2004 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2004年の論文
@ja
2004年論文
@yue
2004年論文
@zh-hant
2004年論文
@zh-hk
2004年論文
@zh-mo
2004年論文
@zh-tw
2004年论文
@wuu
name
Boosting accuracy of automated ...... images for location proteomics
@ast
Boosting accuracy of automated ...... images for location proteomics
@en
Boosting accuracy of automated ...... images for location proteomics
@nl
type
label
Boosting accuracy of automated ...... images for location proteomics
@ast
Boosting accuracy of automated ...... images for location proteomics
@en
Boosting accuracy of automated ...... images for location proteomics
@nl
prefLabel
Boosting accuracy of automated ...... images for location proteomics
@ast
Boosting accuracy of automated ...... images for location proteomics
@en
Boosting accuracy of automated ...... images for location proteomics
@nl
P2860
P356
P1433
P1476
Boosting accuracy of automated ...... images for location proteomics
@en
P2093
Robert F Murphy
P2860
P2888
P356
10.1186/1471-2105-5-78
P407
P577
2004-06-18T00:00:00Z
P5875
P6179
1035585666