Journal of Computer Science & Systems Biology

Biological processes such as contagious disease spread patterns and tumor growth dynamics are modelled using a set of coupled differential equations. Experimental data is usually used to calibrate models so they can be used to make future predictions. In this study, numerical methods were implemented to approximate solutions to mathematical models that were not solvable analytically, such as a SARS model. More complex models such as a tumor growth model involve high-dimensional parameter spaces; efficient numerical simulation techniques were used to search for optimal or close-to-optimal parameter values in the equations. Runge-Kutta methods are a group of explicit and implicit numerical methods that effectively solve the ordinary differential equations in these models. Effects of the order and the step size of Runge-Kutta methods were studied in order to maximize the search accuracy and efficiency in parameter spaces of the models. Numerical simulation results showed that an order of four gave the best balance between truncation errors and the simulation speed for SIR, SARS, and tumormodels studied in the project. The optimal step size for differential equation solvers was found to be model-dependent.

Real-world problems can be formulated as distributed constraint satisfaction problems. Marine resources are subject to certain constraints relating to their physical design, their interactions and legal requirements. Decision making is a major problem since the resource management is distributed and threatened by socio economic activities and environmental factors. A target species with high consumption demand (rabbitfish) is modelled using a system dynamic model builder as a prey agent of the system and predators as the predator agents, other agents including primary production and fishing and aggregation gears are also used. Primary productivity and Predators through aggregation, exploitation and predation affects the population dynamics of the prey agent. Modelling and simulation helps increase the understanding of the behaviour of the prey fish and help explore the potential effect of different management scenario on the exposure of the prey fish to such constraint violation. This study proposes a multi-agent system (MAS) model simulated to explore the impact of different management decision strategies on a marine ecosystems management problem involving several environmental agents. Focussing on the multiple agents within a dynamic environment facing several distributed environmental constraints. A population growth curve is used to identify the initial state (problem) of the marine ecosystem based on available data and how different decision strategies affect the state as they are implemented (problem solving using constraints). A simulation toolkit (Netlogo V5) is used to model different environmental dynamics, interactions and constraints satisfaction to realise an increase in population for the target species. The proposed model examines distributed data among different government agencies databases and publications. The proposed model is analysed and produce results confirming improved decision support through the use of multi agent systems and distributed constraint satisfaction.

This report explores the contribution of lateral myosin bending to the developed crossbridge force and power stroke. The equipartition theorem and Boltzmann distribution are used to calculate crossbridge force and displacement, consistent with experimental values. Negligible buckling strength of the S2-myosin link means that the muscle crossbridge is effectively a one-way force transducer, a mechanical diode, transmitting axial tension forces only. Crossbridge stiffness surfaces as an important factor. Power-stroke displacement is found to decrease with increasing stiffness, whereas axial force increases. The transverse thermal fluctuations of the myosin molecule are significant. Equipartition is used to calculate the mode amplitudes for myosin bending. Crossbridge axial force Fx and power stroke Δx develop from transverse in-plane fluctuations along the y and z axes. Single and doubleheaded actin-myosin attachment configurations are calculated in detail. Practical applications include the effects of temperature on the flexibility of the myosin molecule stiffness and tension, relevant to man-made fabrication of synthetic muscle using micro-machines. Scaling laws for the S2 bending amplitude depend on mode number, filament length, and stiffness, as (n)-2, (L)2, and (EI)-1.