@inproceedings{344fb168d42e4ce9a8cca7ff7f35c800,
title = "Mining biologically significant co-regulation patterns from microarray data",
abstract = "In this paper, we propose a novel model, namely g-Cluster, to mine biologically significant co-regulated gene clusters. The proposed model can (1) discover extra co-expressed genes that cannot be found by current pattern/tendency-based methods, and (2) discover inverted relationship overlooked by pattern/tendency-based methods. We also design two tree-based algorithms to mine all qualified g-Clusters. The experimental results show: (1) our approaches are effective and efficient, and (2) our approaches can find an amount of co-regulated gene clusters missed by previous models, which are potentially of high biological significance.",
keywords = "Bioinformatics, Clustering, Micro-array data",
author = "Yuhai Zhao and Ying Yin and Guoren Wang",
year = "2006",
doi = "10.1007/11795131\_59",
language = "English",
isbn = "3540362975",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "408--414",
booktitle = "Rough Sets and Knowledge Technology - First International Conference, RSKT 2006, Proceedings",
address = "Germany",
note = "First International Conference on Rough Sets and Knowledge Technology, RSKT 2006 ; Conference date: 24-07-2006 Through 26-07-2006",
}