0

Full Content is available to subscribers

Subscribe/Learn More  >

A Time-Based Approach to Stochastic Modeling of Intracellular Signaling Events

[+] Author Affiliations
Michaëlle N. Mayalu, H. Harry Asada

Massachusetts Institute of Technology, Cambridge, MA

Paper No. DSCC2012-MOVIC2012-8631, pp. 579-583; 5 pages
doi:10.1115/DSCC2012-MOVIC2012-8631
From:
  • ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
  • Volume 1: Adaptive Control; Advanced Vehicle Propulsion Systems; Aerospace Systems; Autonomous Systems; Battery Modeling; Biochemical Systems; Control Over Networks; Control Systems Design; Cooperative and Decentralized Control; Dynamic System Modeling; Dynamical Modeling and Diagnostics in Biomedical Systems; Dynamics and Control in Medicine and Biology; Estimation and Fault Detection; Estimation and Fault Detection for Vehicle Applications; Fluid Power Systems; Human Assistive Systems and Wearable Robots; Human-in-the-Loop Systems; Intelligent Transportation Systems; Learning Control
  • Fort Lauderdale, Florida, USA, October 17–19, 2012
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4529-5
  • Copyright © 2012 by ASME

abstract

This paper presents a modeling framework for an intracellular signaling network based on formalisms derived from the fundamental concepts in probability theory. Cellular behavior is mediated by a network of intracellular protein activations that originate at the membrane in response to stimulation of cell surface receptors. Multiple protein signal transductions occur concurrently through diverse pathways triggered by different extracellular cues. Through crosstalk, these pathways intersect at various node proteins. The state of a particular node protein is dependent on the binding order of molecules from various pathways. The probability of a particular binding order is evaluated using state dependent transduction time probabilities associated with each pathway. In this way, the probability of the cell to be in a given internal state is tracked and used to gain insight into the cell’s phenotypic behavior. A simulation example illustrates the approach. Future work will incorporate the proposed method into the development of a feedback control strategy for the development of an in silico control design of endothelial cell migration during angiogenesis.

Copyright © 2012 by ASME
Topics: Modeling

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In