Agent-based models in translational systems biology

Gary An, Qi Mi, Joyeeta Dutta-Moscato, Yoram Vodovotz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

238 Scopus citations

Abstract

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing.

Original languageEnglish
Pages (from-to)159-171
Number of pages13
JournalWiley Interdisciplinary Reviews: Systems Biology and Medicine
Volume1
Issue number2
DOIs
StatePublished - Sep 2009
Externally publishedYes

Fingerprint

Dive into the research topics of 'Agent-based models in translational systems biology'. Together they form a unique fingerprint.

Cite this