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Multi-scale Modeling Consortium grants funded by
the National Institutes of Health
A multi-scale approach for understanding antigen
presentation in immunity (completed in 2010)
A multi-scale model to predict outcomes of immuno-
modulation and drug therapy during TB
(completed in 2016)
A multi-scale systems pharmacology approach to TB therapy (funded through 2020)
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3-D Simulation of granuloma formation in the lung during M. tuberculosis infection
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IMAG:
This is a
LINK
to the IMAG Wiki site that we can access for meeting
information, webinars, funding information, etc. This wiki contains information relevant to the
IMAG (Interagency Modeling and Analysis Group) and the MSM (Multi-scale Modeling Consortium).
Questions about IMAG and the MSM Consortium can be directed to Dr. Grace
Peng: penggr@mail.nih.gov
Students and Postdoctoral Fellows on this project:
 |
Dr. Simeone Marino, PhD,
Dept of Microbiology and
Immunology,
University of Michigan
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Caitlin Hult,
Dept of Microbiology and
Immunology,
University of Michigan
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Timothy Wessler,
Dept of Chemical Engineering,
University of Michigan
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Joseph Cicchese,
Dept of Chemical Engineering,
University of Michigan
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Louis Joslyn,
Dept of Bioinformatics,
University of Michigan
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Technical support:
People trained under this grant previously:
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Nicolas Cilfone,
Dept of Chemical Engineering, University of Michigan
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Mohammad Fallahi Sichani,
Dept of Chemical Engineering, University of Michigan
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Cory Perry,
Dept of Microbiology and Immunology, University of Michigan
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Chang Gong,
Dept of Bioinformatics,
University of Michigan
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Elsje Piennar,
Dept of Chemical Engineering,
University of Michigan
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Project Summary:
Mycobacterium tuberculosis (Mtb) is the most successful pathogen
known to humans; it is responsible for ~2 million deaths/year and
infects an estimated 1/3 of the world. Despite decades of study, our
understanding of the interplay of various pathogen and immune
processes that allow for different outcomes in tuberculosis (TB),
i.e. primary TB, latency and reactivation TB, remains incomplete.
The hallmark of TB is the formation of a spherical collection of
immune cells in the lung and lymph node that both immunologically
restrains and physically contains the bacteria. Yet bacilli can
survive within granuloma for years. Current therapy requires 6 months
of treatment with multiple antibiotics; immunomodulation may be able
to augment this treatment, shortening treatment time and reducing
side effects. There is a crucial need for an in silico platform to
provide a cost-effective means of predicting the outcome of new
treatment strategies. The long-term goals of this project are to
integrate knowledge about immune system dynamics in these organs into
a realistic, multi-scale, multi-organ model of the immune response
during Mtb infection and to use this model to identify optimal
approaches for immunomodulation/antibiotic therapy. The specific aims
are: Aim 1: Incorporate new components (IL-10, bacterial population
dynamics) into our existing multi-scale lung granuloma model, and use
the model to predict factors affecting control of infection in the
lung. Aim 2: Incorporate new information (lymph node anatomy, key
cytokines, bacterial populations) into our existing multi-scale lymph
node model, and use the model to predict factors leading to
initiation of the immune response and granuloma formation and
maintenance in a lymph node. Aim 3. Build a multi-compartment,
multi-scale model that includes the models of Aims 1 and 2 and
trafficking events between the organs, and use this model to predict
infection control and pathology at the level of individual granulomas
during immunodulation/antibiotic therapy. Data generated herein from
non-human primates will inform our models and be used to validate
predictions. Our systems biology approach - incorporating both
computational and experimental tools - will allow us to predict and
test hypotheses regarding key mechanisms that influence immunity to
TB. Our interdisciplinary approach will also serve the broader
community of researchers investigating areas related to TB, immunity
and multi-scale modeling by providing data and tools that will be
made readily available.
Disclaimer: The reprints available here are provided for your
personal use only and may not be used for any commercial purpose
without prior written permissions from the paper's publisher and
author. The violation is subject to the U.S. Copyright Act of 1976,
Title 17 U.S.C.
Publications:
1) Publications derived from this project:
Qin, S, Junecko, B, Lucero, c, Klamar, C, Trichel, A, Murphey-Corb, M, Tarwater, P, Kirschner, D, Reinhart, T.,
Simian immunodeficiency Virus Infection Potently Modulates Chemokine Networks and Immune Environments in Hilar
Lymph Nodes of Cynomolgus Macaques,
JAIDS, 2013 Aug 1;63(4):428-37,
DOI: 10.1097/QAI.0b013e31828ac85f,
PMID: 23429503,
PMCID: 3688692
Nicholas A. Cilfone, Christopher B. Ford, Simeone Marino, Joshua T. Mattila, Hannah P. Gideon, JoAnne L. Flynn,
Denise E. Kirschner and Jennifer J. Linderman,
Computational Modeling Predicts IL-10 Control of Lesion Sterilization by Balancing Early Host
Immunity-Mediated Antimicrobial Responses with Caseation during Mycobacterium tuberculosis Infection,
J Immunol. 2015 Jan 15;194(2):664-77,
DOI: 10.4049/jimmunol.1400734,
PMID: 25512604,
PMCID: 4283220
Hannah Priyadarshini Gideon, JiaYao Phuah, Amy J. Myers, Bryan D. Bryson, Mark A. Rodgers, M. Teresa Coleman,
Pauline Maiello, Tara Rutledge, Simeone Marino, Sarah M. Fortune, Denise E. Kirschner, Philana Ling Lin,
JoAnne L. Flynn,
Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines
Is Associated with Sterilization,
PLOS: Pathogens, January 22, 2015,
DOI: 10.1371/journal.ppat.1004603,
PMID: 25611466,
PMCID: 4303275
Elsje Pienaar, Nicholas A. Cilfone, Philana Ling Lin, Veronique Dartois, Joshua T. Mattila, J. Russell Butler,
JoAnne L. Flynn, Denise E. Kirschner, Jennifer J. Linderman,
A computational tool integrating host immunity with antibiotic dynamics to study tuberculosis treatment,
Journal of Theoretical Biology (2015), pp. 166-179, published online: 24-DEC-2014,
DOI: 10.1016/j.jtbi.2014.11.021,
PMID: 25497475,
PMCID: 4332617
Simeone Marino, Nicholas A. Cilfone, Joshua T. Mattila, Jennifer J. Linderman, JoAnne L. Flynn, and Denise E. Kirschner,
Macrophage Polarization Drives Granuloma Outcome during Mycobacterium tuberculosis Infection,
Infect. Immun. January 2015 83:324-338;
Accepted manuscript posted online, 3 November 2014,
DOI: 10.1128/IAI.02494-14,
PMID: 25368116,
PMCID: 4288886
Nicholas A. Cilfone, Cory R. Perry, Denise E. Kirschner, Jennifer J. Linderman,
Multi-Scale Modeling Predicts a Balance of Tumor Necrosis Factor-α and Interleukin-10 Controls
the Granuloma Environment during Mycobacterium tuberculosis Infection,
PLOS One, July 15, 2013, 8(7):e68680, Volume 8, Issue 7,
DOI: 10.1371/journal.pone.0068680,
PMID: 23869227,
PMCID: 3711807
Joshua T. Mattila, Olabisi O. Ojo, Diane Kepka-Lenhart, Simeone Marino, Jin Hee Kim, Seok Yong Eum, Laura E. Via,
Clifton E. Barry III, Edwin Klein, Denise E. Kirschner, Sidney M. Morris, Jr., Philana Ling Lin, JoAnne L. Flynn,
Microenvironments in Tuberculous Granulomas Are Delineated by Distinct Populations of Macrophage Subsets and Expression of Nitric Oxide
Synthase and Arginase Isoforms,
J Immunol 2013 191:773-784; published ahead of print June 7, 2013,
DOI: 10.4049/jimmunol.1300113,
PMID: 23749634,
PMCID: 3746594
Myers AJ, Marino S, Kirschner DE, Flynn JL,
Inoculation Dose of Mycobacterium tuberculosis Does Not Influence Priming of T Cell Responses in Lymph Nodes,
J Immunol. 2013 Apr 1 [Epub ahead of print],
DOI: 10.4049/jimmunol.1203465,
PMID: 23547119,
PMCID: 3674545
(Authors)
(Title),
(Reference),
DOI: doi-url,
PMID: 12345678,
PMCID: 7654321
M. El-Kebir, M. van der Kuip, A.M. van Furth, D.E. Kirschner,
Computational modeling of tuberculous meningitis reveals an important role for tumor necrosis factor-α,
JTB 2013, pp 43-53,
DOI: 10.1016/j.jtbi.2013.03.008,
PMID: 23542051,
PMCID: 3821557
Giorgio Guzzetta, Denise Kirschner,
The Roles of Immune Memory and Aging in Protective Immunity and Endogenous Reactivation of Tuberculosis,
PLOS 2013,
DOI: 10.1371/journal.pone.0060425,
PMID: 23580062,
PMCID: 3620273
Repasy T, Lee J, Marino S, Martinez N, Kirschner DE, Hendricks G, Baker S, Wilson AA, Kotton DN, Kornfeld H,
Intracellular Bacillary Burden Reflects a Burst Size for Mycobacterium tuberculosis In Vivo,
PLOS Pathogens 2013,
DOI: 10.1371/journal.ppat.1003190,
PMID: 12345678,
PMCID: 7654321
Fallahi-Sichani M, Marino S, Flynn JL, Linderman JJ, Kirschner DE.,
A systems biology approach for understanding granuloma
formation and function in tuberculosis,
Editors: Johnjoe McFadden, Dany Beste and Andrzej Kierzek,
Systems Biology of Tuberculosis, Springer (NY) 2013,
DOI: 10.1007/978-1-4614-4966-9_7,
PMID: (exempt),
PMCID: (exempt)
The website of the book that contains the above article:
Systems Biology of Tuberculosis
Marino S, Fallahi-Sichani M, Linderman JJ, Kirschner DE,
Mathematical models of anti-TNF therapies and their correlation with tuberculosis,
In Antibody-mediated Drug Delivery Systems: Concepts, Technology and Applications, Y. Pathak and S. Benita, eds., John Wiley and Sons, Inc., 2012,
Hoboken, New Jersey, 83-104, Published Online: 23 APR 2012,
DOI: 10.1002/9781118229019.ch5,
PMID: (exempt),
PMCID: (exempt)
Fallahi-Sichani M, Linderman JJ, Kirschner DE,
NF-kB signaling dynamics play a key role in infection control in tuberculosis,
Frontiers in Physiology, June 2012, Volume 3, Article 170,
DOI: 10.3389/fphys.2012.00170,
PMID: 22685435,
PMCID: 3368390
Fallahi-Sichani M, Flynn JL, Linderman JJ, Kirschner DE,
Differential risk of tuberculosis reactivation among anti-TNF therapies is due to drug binding kinetics and
permeability and not apoptotic and cytolytic activities,
J. Immunology, 2012, The Journal of Immunology, April 1, vol. 188, no. 7, pp. 3169-3178,
DOI: 10.4049/jimmunol.1103298,
PMID: 22379032,
PMCID: 3311778
Supplemental Information - Supplement1
Gregg S. Davis, Simeone Marino, Carl F. Marrs, Janet R. Gilsdorf, Suzanne Dawid, Denise E. Kirschner, Phase variation and host immunity against high molecular weight (HMW) adhesins shape population dynamics of nontypeable Haemophilus influenzae within human hosts, Journal of Theoretical Biology 355 (2014) 208-218, DOI: 10.1016/j.jtbi.2014.04.010, PMID: 24747580, PMCID: 4089356
Chang Gong, Jennifer J. Linderman, Denise Kirschner, Harnessing the heterogeneity of T cell differentiation fate to fine-tune generation of effector and memory T cells, Front. Immunol. 5:57, DOI: 10.3389/fimmu.2014.00057, PMID: 24600448, PMCID: 3928592
This article was one of the most viewed Frontiers in Immunology research articles in February 2014!
Link: Frontiers top viewed immunology research articles blog
Chang Gong, Joshua T. Mattila, Mark Miller, JoAnne L. Flynn, Jennifer J. Linderman, D. Kirschner, Predicting lymph node output efficiency through systems biology, Journal of Theoretical Biology, Volume 335, October 21 2013, Pages 169-184, ePUB: June 29, 2013, DOI: 10.1016/j.jtbi.2013.06.016, PMID: 23816876, PMCID: 3783027
Denise E. Kirschner, C. Anthony Hunt, Simeone Marino, Mohammad Fallahi-Sichani, and Jennifer J. Linderman, Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models. WIREs Syst Biol Med 2014, 6:289-309, DOI: 10.1002/wsbm.1270, PMID: 24810243, PMCID: 4102180
Nicholas A. Cilfone, Denise E. Kirschner, Jennifer J. Linderman, Strategies for Efficient Numerical Implementation of Hybrid Multi-scale Agent-Based Models to Describe Biological Systems. WIREs Syst Biol Med 2014, 6:289-309, DOI: 10.1007/s12195-014-0363-6, PMID: (Pending), PMCID: (n/a)
2) Publications resulting from second grant period:
Guzzetta, G, Ajelli, M, Yang, Z, Merler, S, Furlanello, C,
Kirschner, D.
Modeling socio-demography to capture TB transmission in
a low burden setting,
J. Theor. Biology, Nov 21 2011. 289:197-205.,
PMID: 21906603,
PMCID: 3208139
Fallahi-Sichani M, Flynn JL, Linderman JJ, Kirschner DE,
Differential risk of tuberculosis reactivation among anti-TNF
therapies is due to drug binding kinetics and permeability and not
apoptotic and cytolytic activities,
J. Immunology, 2012, The Journal of Immunology, April 1, vol. 188, no. 7, pp. 3169-3178,
DOI: doi:10.4049/jimmunol.1103298,
PMID: 22379032,
PMCID: 352958
Supplemental Information -
Supplement1
Marino S, Fallahi-Sichani M, Linderman JJ, Kirschner DE,
Mathematical models of anti-TNF therapies and their correlation with tuberculosis,
In Antibody-mediated Drug Delivery Systems: Concepts, Technology and Applications, Y.
Pathak and S. Benita, eds., John Wiley and Sons, 2011, Published Online: 23 APR 2012,
DOI: 10.1002/9781118229019.ch5,
PMID: (exempt),
PMCID: (exempt)
Fallahi-Sichani M, Marino S, Flynn JL, Linderman JJ, Kirschner
DE. ,
A systems biology approach for understanding granuloma formation
and function in tuberculosis, Systems Biology of Tuberculosis
,
Springer, in press 2012. PMCID: not available yet.
Fallahi-Sichani M, Kirschner DE, Linderman JJ.,
NF-kB signaling dynamics play a key role in infection control in tuberculosis,
Front Physiol. 2012;3:170. Epub 2012 Jun 6.,
DOI: 10.3389/fphys.2012.00170,
PMID: 22685435,
PMCID: 3368390
3) Publications resulting from first grant period:
Ray JCJ,
Wang, J
Chan J,
Kirschner D.
The timing of TNF and IFN-Gamma signaling affects macrophage activation strategies during
Mycobacterium tuberculosis infection,
The Journal of Theoretical Biology, 2008, Vol 252, pp. 24-38. PMID:18321531, PMCID:2459258
Soumya D,
Chakravarty SD,
Zhu G,
Tsai MC,
Mohan VP,
Marino S,
Kirschner DE,
Huang B,
Flynn J,
Chan J,
Tumor Necrosis Factor Blockade in Chronic Murine Tuberculosis Enhances Granulomatous In
flammation and Disorganizes Granulomas in the Lungs,
Infection and Immunity, 2008, p. 916-926 Vol. 76, No. 3., PMID: 18212087, PMCID: n/a, NIHMSID: n/a
Bauer A,
Marino S,
Hogue I,
Kirschner D,
The effects of HIV-1 on latent TB infection,
Mathematical Models of Natural Phenomenon, Vol. 3, No. 7, 2008, pp. 229-266. PMID: n/a, PMCID: n/a, NIHMSID: n/a
Ray JCJ,
Flynn JL,
Kirschner D,
A Synergy between Individual TNF-Dependent Functions Determines Granuloma Performance for Controlling Mycobacterium tuberculosis,
Infection. J. Immunology 182 : 3706-3717, 2009. PMID: 19265149, PMCID: n/a, NIHMSID: n/a
Fallahi-Sichani M, Linderman JJ,
Lipid raft-mediated regulation of G-protein
coupled receptor signaling by ligands which influence receptor dimerization:
A computational study,
PLOS One 4 : e6604, 2009. PMID: n/a, PMCID: 2719103
Ito T, Schaller MA, Hogaboam CM, Standiford TJ, Sandor M, Lukacs NW, Chensure
SW, Kunkel SL.
TLR9 regulates the mycobacteria-elicited pulmonary granulomatous immune response in mice through DC-derived Notch
ligand Delta-like 4
,
J Clin Invest 119:33-46, 2009, PMID: 19075396, PMCID: n/a, NIHMSID: n/a
Ito T,
Schaller MA,
Raymond T,
Joshi AD,
Frantz FG,
Carson WF,
Hogaboam C,
Lukacs NW,
Standiford TJ,
Phan SH,
Chensue SW,
Kunkel SL,
Toll-like receptor 9 activation is a key mechanism for the
maintenance of chronic lung inflammation,
Am J Respir Crit Care Med 180 : 1227-1238, 2009, PMID: 19797157, PMCID: n/a, NIHMSID: n/a
D'Souza R,
Lysenko M,
Marino S,
Kirschner D,
Data-parallel algorithms for agent-based model simulations of
tuberculosis on graphics processing units,
The Proceedings of SpringSim'09 - Agent-Directed Simulation, 2009,
PMID: n/a, PMCID: n/a, NIHMSID: n/a
Kirschner DE, Linderman JJ,
Mathematical and computational approaches can
complement experimental studies of host pathogen interactions,
Cellular Microbiology, 11(4): 531-539, 2009, PMID: 19134115, PMCID: 2720090
Fallahi-Sichani M,
Flynn JL,
Linderman JJ,
Kirschner DE,
Differential risk of
tuberculosis reactivakinetics and permeafor publication,
(submitted), PMID: n/a, PMCID: n/a
Windish, H.P., P.L. Lin, J.T. Mattila, A.M. Green, E. O. Onuoha, L.P. Kane, J. L. Flynn.
Aberrant TGF-Beta signaling reduces T regulatory cells in ICAM-1 deficient mice,
increasing the inflammatory response to Mycobacterium tuberculosis
,
J. Leukocyte Biol. 86(3): 713-25, 2009. PMID: n/a, PMCID: 2796623
Lin PL, Rodgers M, Smith L, Bigbee M, Myers A, Bigbee C, Chiosea I, Capuano SV,
Fuhrman C, Klein E, Flynn JL,
Quantitative comparison of active and latent tuberculosis
in the cynomolgus macaque model,
Infect. Immun. 77: 4631-4642. 2009, PMID: 19620341, PMCID: 2747916
Linderman JJ, Riggs T, Pande M, Miller M, Marino S, Kirschner DE,
Characterizing the dynamics of CD4+ T cell
priming within a lymph node,
J. Immunology 184 : 2873 – 2885, 2010, PMID: 20154206, PMCID: n/a, NIHMSID: 217408
Jovic A, Howell B, Cote M, Wade SM, Mehta K, Miyawaki A, Neubig RR, Linderman
JJ, Takayama S,
Phase-locked signals elucidate circuit architecture
of an oscillatory pathway,
PLoS Computational Biology 6(12) e1001040, 2010. PMID: n/a, PMCID: 3009597
Fallahi-Sichani M,
Schaller MA,
Kirschner DE,
Kunkel SL,
Linderman JJ,
Identification of key processes that control tumor necrosis factor availability in a
tuberculosis granuloma,
PLoS Computational Biology 6(5) : e1000778, 2010, e1000778.doi:10.1371/ journal.pcbi.1000778,
PMID: 20463877, PMC2865521
Kirschner D, Young D, Flynn J,
Tuberculosis: Global Approaches to a Global
Disease,
Current Opinion in Biotechnology, 21:524-531. 2010, PMID: 20637596, PMCID: 2943033
Einarsdottir T, Lockhart E, Flynn JL,
Cytotoxicity and secretion of IFN-Gamma are carried out by distinct CD8 T cells during
Mycobacterium tuberculosis infection,
Infect. Immun. 77, 4621-4630, PMID: 19667047, PMC: 2747936
Lin PL, Myers A, Smith L, Bigbee C, Bigbee M, Fuhrman C, Grieser H, Chiosea I,
Voitenek NN, Capuano SV, Klein E, Flynn JL,
TNF neutralization results in disseminated disease during acute and latent M.
tuberculosis infection with normal granuloma structure,
Arthritis Rheum 62(2): 340-50, 2010, PMID: 2011239, PMCID: n/a, NIHMSID: n/a
Lin PL, Flynn JL
Brief Review: Understanding latent tuberculosis: a
moving target,
Journal of Immunology, 2010, 185:15-22. PMID: 20562268, PMCID: n/a, NIHMSID: n/a
Marino M, Myers A, Flynn JL, Kirschner DE,
TNF and IL-10 are major factors in modulation of the phagocytic cell environment
in lung and lymph node in tuberculosis: a next generation two compartmental model,
J. Theor. Biology 265 : 586-598, 2010, PMID: 20510249, PMCID: n/a, NIHMSID: n/a
Green A, Mattila JT, Bigbee CL, Bongers KS, Lin PL, Flynn JL,
CD4 Regulatory T cells in a Cynomolgus Macaque Model of Mycobacterium
tuberculosis Infection,
J. Infect. Dis. 202(4): 533-41, 2010, PMID: 20617900, PMCID: n/a, NIHMSID: n/a
Russell DG, Barry CE, Flynn JL,
Tuberculosis: What we don’t know can,
and does, hurt us,
Science 328 : 852-856, 2010, PMID: 20466922 PMCID: 2872107
Marino S, Linderman JJ, Kirschner DE,
A Multi-faceted Approach to Modeling the immune response in Tuberculosis,
Systems Biology and Medicine 3(4), 479-489, 2011, PMID: n/a, PMCID: 3110521
Comisar WA, Mooney DJ, Linderman JJ,
Integrin organization: Linking adhesion
ligand nanopatterns with altered cell responses,
J. Theor. Biol., 274 : 120-130, 2011, PMID: n/a, PMCID: 3056075
Fallahi-Sichani M, El-Kebir M, Marino S, Kirschner DE, Linderman JJ,
Multi-scale computational modeling reveals a critical role for TNF receptor dynamics in
tuberculosis granuloma formation,
J. Immunology 186 : 3472-3483, 2011, PMID: n/a, PMCID: 3127549
Marino S, El-Kebir M, Kirschner D,
A hybrid multi-compartmental model of granuloma formation and T cell
priming in tuberculosis,
J. Theor. Biology: 280: 50-62, 2011, PMID: n/a, PMCID: n/a, NIHMSID: n/a
Flynn JL, Chan J, Lin PL,
Macrophages and control of granulomatous
inflammation in tuberculosis,
Mucosal Immunology, 2011, 4(3):271-8, 2011, PMID: 21430653, PMID: 21430653, NIHMSID: n/a
Guzzetta, G, Ajelli, M, Yang, Z, Merler, S, Furlanello, C,
Kirschner, D.
Modeling socio-demography to capture TB transmission in
a low burden setting,
J. Theor. Biology, Nov 21 2011. 289:197-205.,
PMID: 21906603,
PMCID: 3208139
Stolberg,VR, Chiu BC, Schmidt BM, Kunkel SL, Sandor M, Chensue SW,
CC-Chemokine receptor 4 contributes to innate NK and chronic stage T helper cell
recall responses during Mycobacterium bovis infection,
Am J Pathol 178: 233-244, 2011, PMID: n/a, PMCID: n/a, NIHMSID: n/a
T, Crson WF, Cavassani KA, Connett JM, Kunkel SL,
CCR6 as a mediator of immunity in the lung and gut,
Exp Cell Res 317 : 613-619, 2011, PMID: 21376174, PMCID: n/a, NIHMSID: n/a
Jovic, A, Wade SM, Miyawaki A, Neubig RR, Linderman JJ, Takayama S
Hi-Fi transmission of periodic signals amid cell-to-cell variability,
Molecular BioSystems 7: 2238-2244, 2011, PMID: 21559542, PMCID: n/a, NIHMSID: n/a
Mirsky HP, Miller M, Linderman JJ, Kirschner DE,
Systems biology approaches to understanding immune cell dynamics in
lymph nodes during infection,
J. Theor. Biology, 2011, in press, PMID: n/a, PMCID: n/a, NIHMSID: n/a
Jovic A, Takayama S, Linderman JJ,
Using microfluidics, real-time imaging and mathematical modeling to
study GPCR "signaling", in G protein-coupled receptors:
From Structure to Function ,
(J. Giraldo and J-P Pin, eds.), The Royal Society of Chemistry,
2011, PMID: n/a, PMCID: n/a, NIHMSID: n/a
Marino S, Fallahi-Sichani M, Linderman JJ, Kirschner DE,
Mathematical models of anti-TNF therapies and their correlation with tuberculosis,
In Antibody-mediated Drug Delivery Systems: Concepts, Technology and Applications, Y.
Pathak and S. Benita, eds., John Wiley and Sons, 2011, Published Online: 23 APR 2012,
DOI: doi:10.1002/9781118229019.ch5,
PMID: n/a,
PMCID: n/a
Modeling Methods and Tools:
Ordinary Differential Equations (several non-linear types, all continuous,
determistic approaches) and Agent-based Model (stochastic, discrete
approach)
Software Development:
Languages and Tools:
C++/C OOP, JAVA
Software Sharing Programs:
MATLAB codes and documentation for shareware analysis tools created
by our group.
http://malthus.micro.med.umich.edu/MSM/shareware
SBML format of Models:
To make our models "sharing-friendly", we have prepared SBML format
for the models in the papers in the following
link that are derived from this study:
http://malthus.micro.med.umich.edu/MSM/sbml
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