@inproceedings{159b010671784a3fa0404a4922db5a72,
title = "A novel method for mining temporally dependent association rules in three-dimensional microarray datasets",
abstract = "Microarray data analysis is a very popular topic of current studies in bioinformatics. Most of the existing methods are focused on clustering-related approaches. However, the relations of genes cannot be generated by clustering mining. Some studies explored association rule mining on microarray, but there is no concrete framework proposed on three-dimensional gene-sample-time microarray datasets yet. In this paper, we proposed a temporal dependency association rule mining method named 3D-TDAR-Mine for three-dimensional analyzing microarray datasets. The mined rules can represent the regulated-relations between genes. Through experimental evaluation, our proposed method can discover the meaningful temporal dependent association rules that are really useful for biologists.",
keywords = "Association rule mining, Data mining, Gene expression analysis, Microarray",
author = "Liu, {Yu Cheng} and Lee, {Chao Hui} and Chen, {Wei Chung} and Shin, {J. W.} and Hsu, {Hui Huang} and S. Tseng",
year = "2010",
month = dec,
day = "1",
doi = "10.1109/COMPSYM.2010.5685410",
language = "English",
isbn = "9781424476404",
series = "ICS 2010 - International Computer Symposium",
pages = "759--764",
booktitle = "ICS 2010 - International Computer Symposium",
note = "2010 International Computer Symposium, ICS 2010 ; Conference date: 16-12-2010 Through 18-12-2010",
}