DSpace at School of Computing, NUS: Item 1900.100/2780

Please use this identifier to cite or link to this item: http://hdl.handle.net/1900.100/2780

Title:	Finding Time-lagged 3D Clusters
Authors:	XU, Xin LU, Ying TAN, Kian-Lee TUNG, Anthony K. H.
Issue Date:	19-Jun-2008
Series/Report no.:	;TRB6/08
Abstract:	Existing 3D clustering algorithms on $gene\times sample\times time$ expression data do not consider the \emph{time lags} between correlated gene expression patterns. Besides, they either ignore the correlation on \emph{time subseries}, or disregard the \emph{continuity} of the time series, or only validate pure shifting or pure scaling coherent patterns instead of the general \emph{shifting-and-scaling patterns}. In this paper, we propose a novel 3D cluster model, $S^2D^3$ Cluster, to address these problems, where $S^2$ reflects the shifting-and-scaling correlation and $D^3$ the 3-Dimensional $gene\times sample\times time$ data. Within the $S^2D^3$ Cluster model, expression levels of genes are shifting-and-scaling coherent in both sample subspace and time subseries with arbitrary time lags. We develop a 3D clustering algorithm, $LagMiner$, for identifying interesting $S^2D^3$ Clusters that satisfy the constraints of regulation ($\gamma$), coherence ($\epsilon$), minimum gene numb...
URI:	http://hdl.handle.net/1900.100/2780
Appears in Collections:	Technical Reports

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