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BMCBI
2007
146views more  BMCBI 2007»
14 years 12 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
BMCBI
2010
134views more  BMCBI 2010»
14 years 12 months ago
ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data
Background: Many high-throughput genomic experiments, such as Synthetic Genetic Array and yeast two-hybrid, use colony growth on solid media as a screen metric. These experiments ...
John C. Dittmar, Robert J. D. Reid, Rodney Rothste...
ICNC
2005
Springer
15 years 5 months ago
Line-Based PCA and LDA Approaches for Face Recognition
Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques are important and well-developed area of image recognition and to date many linear discriminati...
Vo Dinh Minh Nhat, Sungyoung Lee
CIVR
2007
Springer
119views Image Analysis» more  CIVR 2007»
15 years 6 months ago
An in-memory relevance feedback technique for high-performance image retrieval systems
Content-based image retrieval with relevant feedback has been widely adopted as the query model of choice for improved effectiveness in image retrieval. The effectiveness of thi...
Ning Yu, Khanh Vu, Kien A. Hua
ML
2006
ACM
142views Machine Learning» more  ML 2006»
14 years 11 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....