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BMCBI
2008
115views more  BMCBI 2008»
14 years 12 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan
IJCSS
2006
116views more  IJCSS 2006»
14 years 12 months ago
Extracting Motor Unit Firing Information by Independent Component Analysis of Surface Electromyogram: A Preliminary Study Using
Decomposition of electromyogram (EMG) provides a valuable means of obtaining motor unit recruitment and firing rate information. The feasibility of decomposing surface EMG signals...
Ping Zhou, M. M. Lowery, W. Zev Rymer
BMCBI
2010
133views more  BMCBI 2010»
14 years 12 months ago
New components of the Dictyostelium PKA pathway revealed by Bayesian analysis of expression data
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...
CVPR
2005
IEEE
16 years 1 months ago
Representational Oriented Component Analysis (ROCA) for Face Recognition with One Sample Image per Training Class
Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....
ECCV
2002
Springer
16 years 1 months ago
Principal Component Analysis over Continuous Subspaces and Intersection of Half-Spaces
Abstract. Principal Component Analysis (PCA) is one of the most popular techniques for dimensionality reduction of multivariate data points with application areas covering many bra...
Anat Levin, Amnon Shashua