Type of Document Dissertation Author Veliz-Cuba, Alan A. URN etd-07092010-144024 Title The Algebra of Systems Biology Degree PhD Department Genetics, Bioinformatics, and Computational Biology Advisory Committee
Advisor Name Title Laubenbacher, Reinhard C. Committee Chair Burns, John A. Committee Member Jarrah, Abdul Salam Committee Member Mortveit, Henning S. Committee Member Tyler, Brett M. Committee Member Keywords
- Systems Biology
- Finite Dynamical Systems
- Reverse Engineering
- Model Reduction
- Finite Fields
- Polynomial Algebra
- Discrete Models
- Mathematical Biology
Date of Defense 2010-07-05 Availability unrestricted AbstractIn order to understand biochemical networks we need to know not only how their parts
work but also how they interact with each other. The goal of systems biology is to look
at biological systems as a whole to understand how interactions of the parts can give rise
to complex dynamics. In order to do this efficiently, new techniques have to be developed.
This work shows how tools from mathematics are suitable to study problems in systems
biology such as modeling, dynamics prediction, reverse engineering and many others. The
advantage of using mathematical tools is that there is a large number of theory, algorithms
and software available. This work focuses on how algebra can contribute to answer questions
arising from systems biology.
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