Paul Macklin
Paul Macklin
Associate Dean for Undergraduate Education - Luddy School - Indiana University
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Nonlinear modelling of cancer: bridging the gap between cells and tumours
JS Lowengrub, HB Frieboes, F Jin, YL Chuang, X Li, P Macklin, SM Wise, ...
Nonlinearity 23 (1), R1, 2009
Multiscale Cancer Modeling
TS Deisboeck, Z Wang, P Macklin, V Cristini
Annual Review of Biomedical Engineering 13, 127-155, 2011
Multiscale modelling and nonlinear simulation of vascular tumour growth
P Macklin, S McDougall, ARA Anderson, MAJ Chaplain, V Cristini, ...
Journal of mathematical biology 58 (4), 765-798, 2009
The human body at cellular resolution: the NIH Human Biomolecular Atlas Program
Caltech-UW TMC Cai Long lcai@ caltech. edu 21 b Shendure Jay 9 Trapnell Cole ...
Nature 574 (7777), 187-192, 2019
PhysiCell: an Open Source Physics-Based Cell Simulator for 3-D Multicellular Systems
A Ghaffarizadeh, R Heiland, SH Friedman, SM Mumenthaler, P Macklin
PLoS Computational Biology 14 (2), e1005991, 2018
A review of cell-based computational modeling in cancer biology
J Metzcar, Y Wang, R Heiland, P Macklin
JCO clinical cancer informatics 2, 1-13, 2019
Computer simulation of glioma growth and morphology
HB Frieboes, JS Lowengrub, S Wise, X Zheng, P Macklin, EL Bearer, ...
Neuroimage 37, S59-S70, 2007
Patient-calibrated agent-based modelling of ductal carcinoma in situ (DCIS): From microscopic measurements to macroscopic predictions of clinical progression
P Macklin, ME Edgerton, AM Thompson, V Cristini
J. Theor. Biol. 301, 122-140, 2012
Nonlinear simulation of the effect of microenvironment on tumor growth
P Macklin, J Lowengrub
Journal of theoretical biology 245 (4), 677-704, 2007
The cancer microbiome: distinguishing direct and indirect effects requires a systemic view
JB Xavier, VB Young, J Skufca, F Ginty, T Testerman, AT Pearson, ...
Trends in cancer 6 (3), 192-204, 2020
The 2019 mathematical oncology roadmap
RC Rockne, A Hawkins-Daarud, KR Swanson, JP Sluka, JA Glazier, ...
Physical biology 16 (4), 041005, 2019
Evolving interfaces via gradients of geometry-dependent interior Poisson problems: application to tumor growth
P Macklin, J Lowengrub
Journal of Computational Physics 203 (1), 191-220, 2005
A new ghost cell/level set method for moving boundary problems: application to tumor growth
P Macklin, JS Lowengrub
Journal of scientific computing 35, 266-299, 2008
PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling
G Letort, A Montagud, G Stoll, R Heiland, E Barillot, P Macklin, A Zinovyev, ...
Bioinformatics 35 (7), 1188-1196, 2019
An improved geometry-aware curvature discretization for level set methods: application to tumor growth
P Macklin, J Lowengrub
journal of Computational Physics 215 (2), 392-401, 2006
BioFVM: an efficient, parallelized diffusive transport solver for 3-D biological simulations
A Ghaffarizadeh, SH Friedman, P Macklin
Bioinformatics, 2015
Digital twins for predictive oncology will be a paradigm shift for precision cancer care
T Hernandez-Boussard, P Macklin, EJ Greenspan, AL Gryshuk, ...
Nature medicine 27 (12), 2065-2066, 2021
Building digital twins of the human immune system: toward a roadmap
R Laubenbacher, A Niarakis, T Helikar, G An, B Shapiro, RS Malik-Sheriff, ...
NPJ digital medicine 5 (1), 64, 2022
High-throughput cancer hypothesis testing with an integrated PhysiCell-EMEWS workflow
J Ozik, N Collier, JM Wozniak, C Macal, C Cockrell, SH Friedman, ...
BMC bioinformatics 19, 81-97, 2018
Agent-based modeling of cancer stem cell driven solid tumor growth
J Poleszczuk, P Macklin, H Enderling
Stem cell heterogeneity: Methods and protocols, 335-346, 2016
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