Open AccessAgent‐based models in translational systems biology
Author(s) -
An Gary,
Mi Qi,
DuttaMoscato Joyeeta,
Vodovotz Yoram
Publication year - 2009
Publication title -
wiley interdisciplinary reviews: systems biology and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.087
H-Index - 51
eISSN - 1939-005X
pISSN - 1939-5094
DOI - 10.1002/wsbm.45
Subject(s) - computer science , systems biology , context (archaeology) , translational research , modelling biological systems , process (computing) , representation (politics) , computational model , translational science , computational biology , data science , management science , artificial intelligence , biology , engineering , medicine , paleontology , microbiology and biotechnology , politics , political science , law , operating system , pathology
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. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Analytical and Computational Methods > Computational Methods