Chapter title |
Dissecting Cell-Fate Determination Through Integrated Mathematical Modeling of the ERK/MAPK Signaling Pathway.
|
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Chapter number | 29 |
Book title |
ERK Signaling
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Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6424-6_29 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6422-2, 978-1-4939-6424-6
|
Authors |
Sung-Young Shin, Lan K. Nguyen |
Editors |
Gerardo Jimenez |
Abstract |
The past three decades have witnessed an enormous progress in the elucidation of the ERK/MAPK signaling pathway and its involvement in various cellular processes. Because of its importance and complex wiring, the ERK pathway has been an intensive subject for mathematical modeling, which facilitates the unraveling of key dynamic properties and behaviors of the pathway. Recently, however, it became evident that the pathway does not act in isolation but closely interacts with many other pathways to coordinate various cellular outcomes under different pathophysiological contexts. This has led to an increasing number of integrated, large-scale models that link the ERK pathway to other functionally important pathways. In this chapter, we first discuss the essential steps in model development and notable models of the ERK pathway. We then use three examples of integrated, multipathway models to investigate how crosstalk of ERK signaling with other pathways regulates cell-fate decision-making in various physiological and disease contexts. Specifically, we focus on ERK interactions with the phosphoinositide-3 kinase (PI3K), c-Jun N-terminal kinase (JNK), and β-adrenergic receptor (β-AR) signaling pathways. We conclude that integrated modeling in combination with wet-lab experimentation have been and will be instrumental in gaining an in-depth understanding of ERK signaling in multiple biological contexts. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 62% |
Lecturer > Senior Lecturer | 1 | 8% |
Student > Doctoral Student | 1 | 8% |
Other | 1 | 8% |
Researcher | 1 | 8% |
Other | 1 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 8 | 62% |
Agricultural and Biological Sciences | 2 | 15% |
Chemistry | 1 | 8% |
Medicine and Dentistry | 1 | 8% |
Unknown | 1 | 8% |