Finding Time-lagged 3D Clusters
| dc.contributor.author | XU, Xin | en_US |
| dc.contributor.author | LU, Ying | en_US |
| dc.contributor.author | TAN, Kian-Lee | en_US |
| dc.contributor.author | TUNG, Anthony K. H. | en_US |
| dc.date.accessioned | 2008-06-26T10:03:25Z | en_US |
| dc.date.accessioned | 2017-01-23T07:00:11Z | |
| dc.date.available | 2008-06-26T10:03:25Z | en_US |
| dc.date.available | 2017-01-23T07:00:11Z | |
| dc.date.issued | 2008-06-19 | en_US |
| dc.description.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 number ($MinG$), minimum sample subspace size ($MinS$) and minimum time periods length ($MinT$). Experimental results on both synthetic and real-life datasets show that $LagMiner$ is effective, scalable and parameter-robust. While we use gene expression data in this paper, our model and algorithm can be applied on any other data where both spatial and temporal coherence are pursued. | en_US |
| dc.format.extent | 4734051 bytes | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.uri | https://dl.comp.nus.edu.sg/xmlui/handle/1900.100/2780 | en_US |
| dc.language.iso | en | en_US |
| dc.relation.ispartofseries | TRB6/08 | en_US |
| dc.title | Finding Time-lagged 3D Clusters | en_US |
| dc.type | Technical Report | en_US |