TY - JOUR
T1 - Modeling intercellular interactions in early Mycobacterium infection
AU - Warrender, Christina
AU - Forrest, Stephanie
AU - Koster, Frederick
N1 - Funding Information:
This publication was made possible by NSF (grants ANIR-9986555, CCR-0331580 CCR-0311686, and DBI-0309147), DARPA (grants F30602-02-1-0146), NIH Grant Number RR-1P20RR18754 from the Institutional Development Award (IDeA) Program of the National Center for Research Resources, P20 GM066283 and NIAID U54 AI057156 subaward 05-082. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NSF, DARPA, or NIH.
PY - 2006/11
Y1 - 2006/11
N2 - Infection with Mycobacterium tuberculosis (Mtb) is characterized by localized, roughly spherical lesions within which the pathogen interacts with host cells. Containment of the infection or progression of disease depends on the behavior of individual cells, which, in turn, depends on the local molecular environment and on contact with neighboring cells. Modeling can help us understand the nonlinear interactions that drive the overall dynamics in this system. Early events in infection are particularly important, as are spatial effects and inherently stochastic processes. We describe a model of early Mycobacterium infection using the CyCells simulator, which was designed to capture these effects. We relate CyCells simulations of the model to several experimental observations of individual components of the response to Mtb.
AB - Infection with Mycobacterium tuberculosis (Mtb) is characterized by localized, roughly spherical lesions within which the pathogen interacts with host cells. Containment of the infection or progression of disease depends on the behavior of individual cells, which, in turn, depends on the local molecular environment and on contact with neighboring cells. Modeling can help us understand the nonlinear interactions that drive the overall dynamics in this system. Early events in infection are particularly important, as are spatial effects and inherently stochastic processes. We describe a model of early Mycobacterium infection using the CyCells simulator, which was designed to capture these effects. We relate CyCells simulations of the model to several experimental observations of individual components of the response to Mtb.
KW - Immunology
KW - Stochastic simulation
KW - Tuberculosis
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U2 - 10.1007/s11538-006-9103-y
DO - 10.1007/s11538-006-9103-y
M3 - Article
C2 - 17086496
AN - SCOPUS:33750735048
SN - 0092-8240
VL - 68
SP - 2233
EP - 2261
JO - Bulletin of mathematical biology
JF - Bulletin of mathematical biology
IS - 8
ER -