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BMCBI
2008
114views more  BMCBI 2008»
15 years 6 months ago
Visualizing and clustering high throughput sub-cellular localization imaging
Background: The expansion of automatic imaging technologies has created a need to be able to efficiently compare and review large sets of image data. To enable comparisons of imag...
Nicholas A. Hamilton, Rohan D. Teasdale
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BMCBI
2008
102views more  BMCBI 2008»
15 years 6 months ago
Response projected clustering for direct association with physiological and clinical response data
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
Sung-Gon Yi, Taesung Park, Jae K. Lee
IPM
2007
143views more  IPM 2007»
15 years 6 months ago
QCS: A system for querying, clustering and summarizing documents
Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particula...
Daniel M. Dunlavy, Dianne P. O'Leary, John M. Conr...
TCBB
2010
136views more  TCBB 2010»
15 years 4 months ago
Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
— The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses ...
Oliver Rübel, Gunther H. Weber, Min-Yu Huang,...
TJS
2010
182views more  TJS 2010»
15 years 4 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari