Modeling emergence in neuroprotective regulatory networks

Antonio P. Sanfilippo, Jereme N. Haack, Jason E. McDermott, Susan L. Stevens, Mary P. Stenzel-Poore

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The use of predictive modeling in the analysis of gene expression data can greatly accelerate the pace of scientific discovery in biomedical research by enabling in silico experimentation to test disease triggers and potential drug therapies. Techniques such as agent-based modeling and multi-agent simulations are of particular interest as they support the discovery of emergent pathways, as opposed to other dynamic modeling approaches such as dynamic Bayesian nets and system dynamics. Thus far, emergence-modeling techniques have been primarily applied at the multi-cellular level, or have focused on signaling and metabolic networks. We present an approach where emergence modeling is extended to regulatory networks and demonstrate its application to the discovery of neuroprotective pathways. An initial evaluation of the approach indicates that emergence modeling provides novel insights for the analysis of regulatory networks which can advance the discovery of acute treatments for stroke and other diseases.

Original languageEnglish (US)
Title of host publicationComplex Sciences - 2nd International Conference, COMPLEX 2012, Revised Selected Papers
EditorsKristin Glass, Richard Colbaugh, Jeffrey Tsao, Paul Ormerod
PublisherSpringer-Verlag
Pages291-302
Number of pages12
ISBN (Print)9783319034720
DOIs
StatePublished - Jan 1 2013
Event2nd International Conference on Complex Sciences, COMPLEX 2012 - Santa Fe, United States
Duration: Dec 5 2012Dec 7 2012

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume126 LNICST
ISSN (Print)1867-8211

Other

Other2nd International Conference on Complex Sciences, COMPLEX 2012
CountryUnited States
CitySanta Fe
Period12/5/1212/7/12

Keywords

  • Agent-based modeling
  • Complex systems
  • Emergence
  • Neuroprotection
  • Regulatory networks
  • Stroke

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Sanfilippo, A. P., Haack, J. N., McDermott, J. E., Stevens, S. L., & Stenzel-Poore, M. P. (2013). Modeling emergence in neuroprotective regulatory networks. In K. Glass, R. Colbaugh, J. Tsao, & P. Ormerod (Eds.), Complex Sciences - 2nd International Conference, COMPLEX 2012, Revised Selected Papers (pp. 291-302). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 126 LNICST). Springer-Verlag. https://doi.org/10.1007/978-3-319-03473-7_26