Doctoral Dissertations

Keywords and Phrases

Cell signaling; Combinatorial complexity; Diffusion; Endocytosis; Ligand- receptor; Systems biology

Abstract

"The main focus of the research is to understand the complex phenomena of cell transduction pathways and cell biology in a single cell. Mathematical modeling and experimental evaluation are widely used approaches for this kind of research. Firstly, A multiscale framework for protein-protein interaction has been established using Brownian dynamics algorithm. Sit specific feature, steric collision, diffusion, co-localization and complex formation with time and space has been included in this spatial modeling framework. By implementation of the time adaptive feature in this framework, the computation time reduces in an order of magnitude compared with traditional modeling framework. This multiscale Brownian framework has been used for the investigation FcεRI aggregation which is an important signaling pathway for immune cells. Using the spatial modeling framework, FcεRI aggregation in the presence of trivalent antigen showed consistent results with current experimental studies. Secondly, the rule-based modeling approach is an excellent way of performing large biochemical network modeling for a single cell as it considers the site-specific features. However, the major difficulty of rule-based modeling approach is combinatorial complexity. In this study, model restructuring approaches have been applied to overcome this problem for cell signaling pathway modeling. These mechanistic modeling approaches are very effective to model large network of signaling pathways together without compromising the accuracy. Finally, Cell size dependent cellular uptake study carried out using confocal microscopy and flow cytometer. To understand the particle uptake behavior with time and steady state condition, reaction-diffusion and kinetics model has been developed in these work. After a detailed analysis of experimental data and models, it showed that total particle uptake is increasing with cell size, however, particle flux is reducing in larger cells"--Abstract, page iv.

Advisor(s)

Barua, Dipak

Committee Member(s)

Wang, Jee-Ching
Park, Joontaek
Barua, Sutapa
Samaranayake, V. A.
Hlavacek, William

Department(s)

Chemical and Biochemical Engineering

Degree Name

Ph. D. in Chemical Engineering

Sponsor(s)

National Science Foundation (U. S.). Division of Chemical, Bioengineering, Environmental and Transport Systems
National Science Foundation (U.S.). Computational and Data-Enabled Science and Engineering
University of Missouri Research Board

Comments

Research presented in this work was supported by the National Science Foundation CBET-CDS&E grant No. 1609642 and the University of Missouri Research Board (UMRB) seed grant.

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2019

Journal article titles appearing in thesis/dissertation

  • A multiscale algorithm for spatiotemporal modeling of multivalent protein protein interaction
  • A spatiotemporal model reveals self limiting FCεRI crosslinking by multivalent antigens
  • Cellular heterogeneity in endocytic nanoparticle uptake: Dissecting the origin using quantitative experiments and modeling
  • Quantitative analysis of the correlation between cell size and cellular uptake of particles
  • Systematic reduction of rule-based model dimension: Application to receptor tyrosine kinase modeling

Pagination

xiv, 138 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2019 Md Shahinuzzaman, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11602

Electronic OCLC #

1119724169

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