Systems biology is a comprehensive quantitative analysis of the manner in
which all the components of a biological system interact functionally along with
time. Mathematical modeling and computational methods are indispensable
in such kind of studies, especially for interpreting and predicting the complex
interactions among all the components so as to obtain some desirable system
properties. System dynamics, system robustness and control method are three
crucial properties in systems biology. In this thesis, the above properties are
studied in four different biological systems.
The outbreak and spread of infectious diseases have been questioned and
studied for years. The spread mechanism and prediction about the disease could
enable scientists to evaluate isolation plans to have significant effects on a particular
epidemic. A differential equation model is proposed to study the dynamics
of HIV spread in a network of prisons. In prisons, screening and quarantining
are both efficient control manners. An optimization model is proposed to study
optimal strategies for the control of HIV spread in a prison system.
A primordium (plural: primordia) is an organ or tissue in its earliest recognizable
stage of development. Primordial development in plants is critical to the
proper positioning and development of plant organs. An optimization model and
two control mechanisms are proposed to study the dynamics and robustness of primordial systems.
Probabilistic Boolean Networks (PBNs) are mathematical models for studying
the switching behavior in genetic regulatory networks. An algorithm is proposed
to identify singleton and small attractors in PBNs which correspond to
cell types and cell states. The captured problem is NP-hard in general. Our
algorithm is theoretically and computationally demonstrated to be much more
efficient than the naive algorithm that examines all the possible states.
The goal of studying the long-term behavior of a genetic regulatory network is
to study the control strategies such that the system can obtain desired properties.
A control method is proposed to study multiple external interventions meanwhile
minimizing the control cost.
Robustness is a paramount property for living organisms. The impact degree
is a measure of robustness of a metabolic system against the deletion of single
or multiple reaction(s). An algorithm is proposed to study the impact degree
in Escherichia coli metabolic system. Moreover, approximation method based
on Branching process is proposed for estimating the impact degree of metabolic
networks. The effectiveness of our method is assured by testing with real-world
Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae and Homo Sapiens
metabolic systems. / published_or_final_version / Mathematics / Doctoral / Doctor of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/174464 |
| Date | January 2012 |
| Creators | Cong, Yang., 丛阳. |
| Contributors | Ching, WK, Tsing, NK |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Source | http://hub.hku.hk/bib/B47752841 |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
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