Chapter title |
Bioinformatics Approach to Identify Novel AMPK Targets
|
---|---|
Chapter number | 7 |
Book title |
AMPK
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7598-3_7 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7597-6, 978-1-4939-7598-3
|
Authors |
Brendan Gongol, Traci Marin, David A. Johnson, John Y.-J. Shyy |
Abstract |
In silico analysis of Big Data is a useful tool to identify putative kinase targets as well as nodes of signaling cascades that are difficult to discover by traditional single molecule experimentation. System approaches that use a multi-tiered investigational methodology have been instrumental in advancing our understanding of cellular mechanisms that result in phenotypic changes. Here, we present a bioinformatics approach to identify AMP-activated protein kinase (AMPK) target proteins on a proteome-wide scale and an in vitro method for preliminary validation of these targets. This approach offers an initial screening for the identification of AMPK targets that can be further validated using mutagenesis and molecular biology techniques. |
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Geographical breakdown
Country | Count | As % |
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Unknown | 3 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Lecturer | 1 | 33% |
Student > Master | 1 | 33% |
Unknown | 1 | 33% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 2 | 67% |
Unknown | 1 | 33% |