Mathematical modelling of partially absorbing boundaries in biological systems
This project presents a mathematical framework for identifying partially permeable biological boundaries, and estimating the rate of absorption of diffusing objects at such a boundary based on limited experimental data. We used partial differential equations (PDEs) to derive probability distribution...
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ndltd-UBC-oai-circle.library.ubc.ca-2429-589072018-01-05T17:29:14Z Mathematical modelling of partially absorbing boundaries in biological systems Iyaniwura, Sarafa Adewale This project presents a mathematical framework for identifying partially permeable biological boundaries, and estimating the rate of absorption of diffusing objects at such a boundary based on limited experimental data. We used partial differential equations (PDEs) to derive probability distribution functions for finding a particle performing Brownian motion in a region. These distribution functions can be fit to data to infer the existence of a boundary. We also used the probability distribution functions together with maximum likelihood estimation to estimate the rate of absorption of objects at the boundaries, based on simulated data. Furthermore, we consider a switching boundary and provide a technique for approximating the boundary with a partially permeable boundary. Science, Faculty of Graduate 2016-08-22T14:41:14Z 2016-08-23T02:02:03 2016 2016-09 Text Thesis/Dissertation http://hdl.handle.net/2429/58907 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ University of British Columbia |
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English |
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description |
This project presents a mathematical framework for identifying partially permeable biological boundaries, and estimating the rate of absorption of diffusing objects at such a boundary based on limited experimental data. We used partial differential equations (PDEs) to derive probability distribution functions for finding a particle performing Brownian motion in a region. These distribution functions can be fit to data to infer the existence of a boundary. We also used the probability distribution functions together with maximum likelihood estimation to estimate the rate of absorption of objects at the boundaries, based on simulated data. Furthermore, we consider a switching boundary and provide a technique for approximating the boundary with a partially permeable boundary. === Science, Faculty of === Graduate |
author |
Iyaniwura, Sarafa Adewale |
spellingShingle |
Iyaniwura, Sarafa Adewale Mathematical modelling of partially absorbing boundaries in biological systems |
author_facet |
Iyaniwura, Sarafa Adewale |
author_sort |
Iyaniwura, Sarafa Adewale |
title |
Mathematical modelling of partially absorbing boundaries in biological systems |
title_short |
Mathematical modelling of partially absorbing boundaries in biological systems |
title_full |
Mathematical modelling of partially absorbing boundaries in biological systems |
title_fullStr |
Mathematical modelling of partially absorbing boundaries in biological systems |
title_full_unstemmed |
Mathematical modelling of partially absorbing boundaries in biological systems |
title_sort |
mathematical modelling of partially absorbing boundaries in biological systems |
publisher |
University of British Columbia |
publishDate |
2016 |
url |
http://hdl.handle.net/2429/58907 |
work_keys_str_mv |
AT iyaniwurasarafaadewale mathematicalmodellingofpartiallyabsorbingboundariesinbiologicalsystems |
_version_ |
1718585343094030336 |