MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Integrated Mechanistic-Empirical Modeling of Cellular Response Based on Intracellular Signaling Dynamics

Author(s)
Mayalu, Michaelle N; Asada, Haruhiko
Thumbnail
Downloadv003t43a002-dscc2013-3806.pdf (1.667Mb)
PUBLISHER_POLICY

Publisher Policy

Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

Terms of use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Metadata
Show full item record
Abstract
A hybrid modeling framework integrating a highly specific mechanistic model with highly abstract empirical model is presented. With the growing interest in the scientific and medical community for identification of therapeutic targets in treatment of disease, it is necessary to develop predictive models that can describe cellular behavior in response to environmental cues. Intracellular signaling pathways form complex networks that regulate cellular response in both health and disease. Mechanistic (or white-box) models of biochemical networks are often unable to explain comprehensive cellular response due to lack of knowledge and/or intractable complexity (especially in events distal from the cell membrane). Empirical (or black-box) models may provide a less than accurate representation of cellular response due to data deficiency and/or loss of mechanistic detail. In the proposed framework, we use a mechanistic model to capture early signaling events and apply the resulting generated internal signals (along with external inputs) to a downstream empirical sub-model. The key construct in the approach is the treatment of a cell's biochemical network as an encoder that creates a functional internal representation of external environmental cues. The signals derived from this representation are then used to inform downstream behaviors. Using this idea, we are able to create a comprehensive framework that describes important mechanisms with sufficient detail, while representing complex or unknown mechanisms in a more abstract form. The model is verified using published biological data describing T-Cells in immune response.
Date issued
2013-10
URI
http://hdl.handle.net/1721.1/118971
Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Journal
Proceedings of the ASME 2013 Dynamic Systems and Control Conference
Publisher
ASME International
Citation
Mayalu, Michaëlle N., and H. Harry Asada. “Integrated Mechanistic-Empirical Modeling of Cellular Response Based on Intracellular Signaling Dynamics.” ASME 2013 Dynamic Systems and Control Conference, 21-23 October, 2013, Palo Alto, California, ASME, 2013, p. V003T43A002. © 2013 by ASME.
Version: Final published version
ISBN
978-0-7918-5614-7

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.