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Nanoscale
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October 31, 2022
Equation learning to identify nano-engineered particle-cell interactions: an interpretable machine learning approach
Stuart T Johnston, Matthew Faria
Journal of the American Chemical Society
|
September 28, 2016
Increasing the Impact of Materials in and beyond Bio-Nano Science
Mattias Björnmalm, Matthew Faria, Frank Caruso
Journal of the Royal Society, Interface
|
July 27, 2018
An analytical approach for quantifying the influence of nanoparticle polydispersity on cellular delivered dose
Stuart T Johnston, Matthew Faria, Edmund J Crampin
Journal of the Royal Society, Interface
|
May 21, 2020
Isolating the sources of heterogeneity in nano-engineered particle-cell interactions
Stuart T Johnston, Matthew Faria, Edmund J Crampin
Nanoscale Advances
|
September 22, 2022
Understanding nano-engineered particle-cell interactions: biological insights from mathematical models
Stuart T Johnston, Matthew Faria, Edmund J Crampin
Nature Nanotechnology
|
January 12, 2020
A few clarifications on MIRIBEL
Matthew Faria, Mattias Björnmalm, Edmund J Crampin, et al.
Royal Society Open Science
|
August 1, 2025
Thermodynamically consistent, reduced models of gene regulatory networks
Michael Pan, Peter J Gawthrop, Matthew Faria, et al.
Langmuir : the ACS Journal of Surfaces and Colloids
|
October 18, 2016
Dynamic Flow Impacts Cell-Particle Interactions: Sedimentation and Particle Shape Effects
Mattias Björnmalm, Matthew Faria, Xi Chen, et al.
Mathematical Biosciences
|
November 5, 2022
On predicting heterogeneity in nanoparticle dosage
Celia V Dowling, Paula M Cevaal, Matthew Faria, et al.
Journal of the Royal Society, Interface
|
September 16, 2025
Quantifying biological heterogeneity in nano-engineered particle-cell interaction experiments
Ryan J Murphy, Matthew Faria, James M Osborne, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 27) with videos related to
Sort By:
Page
of 3
Nanoscale
|
October 31, 2022
Equation learning to identify nano-engineered particle-cell interactions: an interpretable machine learning approach
Stuart T Johnston, Matthew Faria
Journal of the American Chemical Society
|
September 28, 2016
Increasing the Impact of Materials in and beyond Bio-Nano Science
Mattias Björnmalm, Matthew Faria, Frank Caruso
Journal of the Royal Society, Interface
|
July 27, 2018
An analytical approach for quantifying the influence of nanoparticle polydispersity on cellular delivered dose
Stuart T Johnston, Matthew Faria, Edmund J Crampin
Journal of the Royal Society, Interface
|
May 21, 2020
Isolating the sources of heterogeneity in nano-engineered particle-cell interactions
Stuart T Johnston, Matthew Faria, Edmund J Crampin
Nanoscale Advances
|
September 22, 2022
Understanding nano-engineered particle-cell interactions: biological insights from mathematical models
Stuart T Johnston, Matthew Faria, Edmund J Crampin
Nature Nanotechnology
|
January 12, 2020
A few clarifications on MIRIBEL
Matthew Faria, Mattias Björnmalm, Edmund J Crampin, et al.
Royal Society Open Science
|
August 1, 2025
Thermodynamically consistent, reduced models of gene regulatory networks
Michael Pan, Peter J Gawthrop, Matthew Faria, et al.
Langmuir : the ACS Journal of Surfaces and Colloids
|
October 18, 2016
Dynamic Flow Impacts Cell-Particle Interactions: Sedimentation and Particle Shape Effects
Mattias Björnmalm, Matthew Faria, Xi Chen, et al.
Mathematical Biosciences
|
November 5, 2022
On predicting heterogeneity in nanoparticle dosage
Celia V Dowling, Paula M Cevaal, Matthew Faria, et al.
Journal of the Royal Society, Interface
|
September 16, 2025
Quantifying biological heterogeneity in nano-engineered particle-cell interaction experiments
Ryan J Murphy, Matthew Faria, James M Osborne, et al.
Page
of 3