%0 Journal Article
%T Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle
%A Qingfeng Chen
%A Yi-Ping Chen
%J BMC Bioinformatics
%D 2006
%I BioMed Central
%R 10.1186/1471-2105-7-394
%X This paper proposes a framework that can identify the potential correlation, either between the state of isoforms of ¦Á, ¦Â and ¦Ã subunits of AMPK, or between stimulus factors and the state of isoforms. Our approach is to apply item constraints in the closed interpretation to the itemset generation so that a threshold is specified in terms of the amount of results, rather than a fixed threshold value for all itemsets of all sizes. The derived rules from experiments are roughly analyzed. It is found that most of the extracted association rules have biological meaning and some of them were previously unknown. They indicate direction for further research.Our findings indicate that AMPK has a great impact on most metabolic actions that are related to energy demand and supply. Those actions are adjusted via its subunit isoforms under specific physical training. Thus, there are strong co-relationships between AMPK subunit isoforms and exercises. Furthermore, the subunit isoforms are correlated with each other in some cases. The methods developed here could be used when predicting these essential relationships and enable an understanding of the functions and metabolic pathways regarding AMPK.In recent years, there has been a tremendous growth in biological data and the emergence of new, efficient experimental techniques. A variety of genomic and proteomic databases are now publicly accessible over the Internet. However, it is widely recognized that the mere gathering of discrete data is insufficient for us to discover the potential correlations amongst them. The biological interpretation and analysis of these data are crucial. Such biological data not only provides us with a good opportunity for understanding living organisms, but also poses new challenges. This has led us to the development of a new method to analyze the data.Protein kinases' regulation data can be a good foundation for understanding their structure, function, and expression. One goal, in terms of analyzing
%U http://www.biomedcentral.com/1471-2105/7/394