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Full-Text Articles in Physical Sciences and Mathematics
Computationally Modeling Dynamic Biological Systems, Katherine Jarvis
Computationally Modeling Dynamic Biological Systems, Katherine Jarvis
Electronic Theses and Dissertations
Modeling biological systems furthers our understanding of dynamic relationships and helps us make predictions of the unknown properties of the system. The simple interplay between individual species in a dynamic environment over time can be modeled by equation-based modeling or agent- based modeling (ABM). Equation based modeling describes the change in species quantity using ordinary differential equations (ODE) and is dependent on the quantity of other species in the system as well as a predetermined rates of change. Unfortunately, this method of modeling does not model each individual agent in each species over time so individual dynamics are assumed to …
Lexicographic Sensitivity Functions For Nonsmooth Models In Mathematical Biology, Matthew D. Ackley
Lexicographic Sensitivity Functions For Nonsmooth Models In Mathematical Biology, Matthew D. Ackley
Electronic Theses and Dissertations
Systems of ordinary differential equations (ODEs) may be used to model a wide variety of real-world phenomena in biology and engineering. Classical sensitivity theory is well-established and concerns itself with quantifying the responsiveness of such models to changes in parameter values. By performing a sensitivity analysis, a variety of insights can be gained into a model (and hence, the real-world system that it represents); in particular, the information gained can uncover a system's most important aspects, for use in design, control or optimization of the system. However, while the results of such analysis are desirable, the approach that classical theory …
Toward Improving Understanding Of The Structure And Biophysics Of Glycosaminoglycans, Elizabeth K. Whitmore
Toward Improving Understanding Of The Structure And Biophysics Of Glycosaminoglycans, Elizabeth K. Whitmore
Electronic Theses and Dissertations
Glycosaminoglycans (GAGs) are the linear carbohydrate components of proteoglycans (PGs) that mediate PG bioactivities, including signal transduction, tissue morphogenesis, and matrix assembly. To understand GAG function, it is important to understand GAG structure and biophysics at atomic resolution. This is a challenge for existing experimental and computational methods because GAGs are heterogeneous, conformationally complex, and polydisperse, containing up to 200 monosaccharides. Molecular dynamics (MD) simulations come close to overcoming this challenge but are only feasible for short GAG polymers. To address this problem, we developed an algorithm that applies conformations from unbiased all-atom explicit-solvent MD simulations of short GAG polymers …