Doctoral Dissertations

Keywords and Phrases

Cell signaling; Computational biology; Multiscale modeling; Parallelism; Systems biology; Tissue transport

Abstract

"Multiscale nature of a biological system span at many order of magnitudes in time and space. Molecular interaction at lower scale is connected with the higher scale behavior of tissue or organism. Integrating the dynamics and information at different time and space can give a fundamental physiological understanding of the higher level phenomena. But complex features, functions, interconnectivity between different scales and lack of information on the fundamental physiological property make the model difficult and computationally challenging. The multiscale modeling approach can bridge the gap between different scale by a systemic integration of the complex dynamic behavior.

Here, the focus is on developing multiscale modeling approaches to study the dynamic behavior of tissue. First, a multiscale spatiotemporal model is designed to investigate the tissue scale dispersion and penetration of nanoparticles from lower scale particle-cell interaction. The results obtained suggest that the size of nanoparticles may play less significant roles in tissue scale penetration and dispersion. The effect of nanoparticle size is less prominent due to the presence of particle-cell interaction and advection. This scalable spatiotemporal model can simulate the dynamics of drug delivery particles in the extracellular domain of a tissue.

Furthermore, a parallel framework is developed to study the collective behavior of the cell population in a tissue architecture from their intracellular and extracellular reaction kinetics. The framework can model population dynamics at the tissue scale from a single cell biochemical reaction network accurately and efficiently. Finally, the framework's capability is demonstrated by simulating a full-scale model of bacterial quorum sensing, where the dynamics of a population of bacterial cells is dictated by the intercellular communications in a time-evolving growth environment"--Abstract, page iii.

Advisor(s)

Barua, Dipak

Committee Member(s)

Barua, Sutapa
Wang, Jee-Ching
Park, Joontaek
Das, Sajal K.

Department(s)

Chemical and Biochemical Engineering

Degree Name

Ph. D. in Chemical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2019

Pagination

xiii, 115 pages

Note about bibliography

Includes bibliographic references (pages 101-114).

Rights

© 2019 Mohammad Aminul Islam, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11590

Electronic OCLC #

1119724027

Download

Share

 
COinS