Chen Qingfeng, Chen Yi-Ping Phoebe
School of Engineering & Information Technology, Deakin University, Melbourne, Australia.
BMC Bioinformatics. 2006 Aug 30;7:394. doi: 10.1186/1471-2105-7-394.
AMP-activated protein kinase (AMPK) has emerged as a significant signaling intermediary that regulates metabolisms in response to energy demand and supply. An investigation into the degree of activation and deactivation of AMPK subunits under exercise can provide valuable data for understanding AMPK. In particular, the effect of AMPK on muscle cellular energy status makes this protein a promising pharmacological target for disease treatment. As more AMPK regulation data are accumulated, data mining techniques can play an important role in identifying frequent patterns in the data. Association rule mining, which is commonly used in market basket analysis, can be applied to AMPK regulation.
This paper proposes a framework that can identify the potential correlation, either between the state of isoforms of alpha, beta and gamma 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.
AMP 激活的蛋白激酶（AMPK）已成为一种重要的信号转导中间体，可根据能量需求和供应调节新陈代谢。研究运动时 AMPK 亚基的激活和失活程度可为理解 AMPK 提供有价值的数据。特别是，AMPK 对肌肉细胞能量状态的影响使该蛋白成为疾病治疗中有前景的药理学靶点。随着更多 AMPK 调节数据的积累，数据挖掘技术可在识别数据中的频繁模式方面发挥重要作用。常用于市场篮分析的关联规则挖掘可应用于 AMPK 调节。
本文提出了一个框架，该框架可以识别 AMPK 的α、β和γ亚基异构体状态之间，或刺激因素与异构体状态之间的潜在相关性。我们的方法是在封闭解释中将项目约束应用于项集生成，以便根据结果数量指定一个阈值，而不是为所有大小的所有项集指定一个固定阈值。对实验得出的规则进行了大致分析。发现大多数提取的关联规则具有生物学意义，其中一些是以前未知的。它们为进一步研究指明了方向。
我们的研究结果表明，AMPK 对大多数与能量需求和供应相关的代谢作用有很大影响。这些作用在特定体育训练下通过其亚基异构体进行调节。因此，AMPK 亚基异构体与运动之间存在很强的相互关系。此外，亚基异构体在某些情况下相互关联。这里开发的方法可用于预测这些基本关系，并有助于理解 AMPK 的功能和代谢途径。
