Analysis of the in-vitro nanoparticle-cell interactions via support vector regression model
Author
Akbulut, Nur Muhammed
Advisor
Dayanık, Savaş
Date
2013Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
In this research a Support Vector Regression model is developed to understand the
nanoparticle (NP)-cell interactions and to predict the cellular uptake rate of the
nanoparticles, which is the rate of NPs adhered to the cell surface or entered into the
cell. Examination of nanoparticle-cell interaction is important for developing
targeted drug delivery systems and cell-level detection and treatment of diseases.
Cellular uptake rate of NPs depends on NP type, size, shape, surface charge,
concentration and incubation time. Conducting numerous experiments on the
combinations of those variables to understand NP-cell interaction is impractical.
Hence, a mathematical model of the cellular uptake rate will therefore be useful. The
data for this study are obtained from in-vitro NP-healthy cell experiments conducted
by a Nano-Medicine Research Center in Turkey. The proposed support vector
regression model predicts the cellular uptake rate of nanoparticles with respect to
incubation time given the size, charge and concentration properties of NPs.