@inproceedings{97a2030ffb4b40e58747ab5d49c0dc8e,
title = "Mining time-delayed coherent patterns in time series gene expression data",
abstract = "Unlike previous pattern-based biclustering methods that focus on grouping objects on the same subset of dimensions, in this paper, we propose a novel model of coherent cluster for time series gene expression data, namely td-cluster (time-delayed cluster). Under this model, objects can be coherent on different subsets of dimensions if these objects follow a certain time-delayed relationship. Such a cluster can discover the cycle time of gene expression, which is essential in revealing the gene regulatory networks. This work is missed by previous research. A novel algorithm is also presented and implemented to mine all the significant td-clusters. Experimental results from both real and synthetic microarray datasets prove its effectiveness and efficiency.",
author = "Linjun Yin and Guoren Wang and Keming Mao and Yuhai Zhao",
year = "2006",
doi = "10.1007/11811305\_78",
language = "English",
isbn = "3540370250",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "711--722",
editor = "Xue Li and Za{\"i}ane, \{Osmar R.\} and Zhanhuai Li",
booktitle = "Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings",
address = "Germany",
note = "2nd International Conference on Advanced Data Mining and Applications, ADMA 2006 ; Conference date: 14-08-2006 Through 16-08-2006",
}