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https://doi.org/10.1186/1471-2105-7-394
Title: | Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle | Authors: | Chen, Q Chen, Y.-P.P |
Keywords: | AMP-activated protein kinase Co-relationships Disease treatment Itemset generation Market basket analysis Metabolic action Metabolic pathways Physical training Energy management Metabolism Muscle Data mining hydroxymethylglutaryl coenzyme A reductase kinase isoenzyme hydroxymethylglutaryl coenzyme A reductase kinase isoenzyme multienzyme complex protein serine threonine kinase protein subunit alpha chain article beta chain controlled study correlation analysis energy consumption enzyme activity exercise human information processing muscle training prediction protein expression protein function protein metabolism skeletal muscle algorithm computer program diabetes mellitus energy metabolism gene expression regulation genetics mathematical computing metabolism protein subunit signal transduction skeletal muscle Algorithms AMP-Activated Protein Kinases Diabetes Mellitus Energy Metabolism Exercise Gene Expression Regulation, Enzymologic Humans Isoenzymes Mathematical Computing Multienzyme Complexes Muscle, Skeletal Protein Subunits Protein-Serine-Threonine Kinases Signal Transduction Software |
Issue Date: | 2006 | Citation: | Chen, Q, Chen, Y.-P.P (2006). Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle. BMC Bioinformatics 7 : 394. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2105-7-394 | Rights: | Attribution 4.0 International | Abstract: | Background: 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. Results: This paper proposes a framework that can identify the potential correlation, either between the state of isoforms of ?, ? and ? 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. Conclusion: 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. © 2006 Chen and Chen; licensee BioMed Central Ltd. | Source Title: | BMC Bioinformatics | URI: | https://scholarbank.nus.edu.sg/handle/10635/178015 | ISSN: | 14712105 | DOI: | 10.1186/1471-2105-7-394 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
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