Strategic Directions in Object-Oriented Programming

This paper has provided an overview of the field of object-oriented programming. After presenting a historical perspective and some major achievements in the field, four research directions were introduced: technologies integration, software components, distributed programming, and new paradigms. In general there is a need to continue research in traditional areas:\ud (1) as computer systems become more and more complex, there is a need to further develop the work on architecture and design; \ud (2) to support the development of complex systems, there is a need for better languages, environments, and tools; \ud (3) foundations in the form of the conceptual framework and other theories must be extended to enhance the means for modeling and formal analysis, as well as for understanding future computer systems

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Couplerlib: a metadata-driven library for the integration of multiple models of higher and lower trophic level marine systems with inexact functional group matching

End-to-end modelling is a rapidly developing strategy for modelling in marine systems science and management. However, problems remain in the area of data matching and sub-model compatibility. A mechanism and novel interfacing system (Couplerlib) is presented whereby a physical–biogeochemical model (General Ocean Turbulence Model–European Regional Seas Ecosystem Model, GOTM–ERSEM) that predicts dynamics of the lower trophic level (LTL) organisms in marine ecosystems is coupled to a dynamic ecosystem model (Ecosim), which predicts food-web interactions among higher trophic level (HTL) organisms. Coupling is achieved by means of a bespoke interface, which handles the system incompatibilities between the models and a more generic Couplerlib library, which uses metadata descriptions in extensible mark-up language (XML) to marshal data between groups, paying attention to functional group mappings and compatibility of units between models. In addition, within Couplerlib, models can be coupled across networks by means of socket mechanisms. As a demonstration of this approach, a food-web model (Ecopath with Ecosim, EwE) and a physical–biogeochemical model (GOTM–ERSEM) representing the North Sea ecosystem were joined with Couplerlib. The output from GOTM–ERSEM varies between years, depending on oceanographic and meteorological conditions. Although inter-annual variability was clearly present, there was always the tendency for an annual cycle consisting of a peak of diatoms in spring, followed by (less nutritious) flagellates and dinoflagellates through the summer, resulting in an early summer peak in the mesozooplankton biomass. Pelagic productivity, predicted by the LTL model, was highly seasonal with little winter food for the higher trophic levels. The Ecosim model was originally based on the assumption of constant annual inputs of energy and, consequently, when coupled, pelagic species suffered population losses over the winter months. By contrast, benthic populations were more stable (although the benthic linkage modelled was purely at the detritus level, so this stability reflects the stability of the Ecosim model). The coupled model was used to examine long-term effects of environmental change, and showed the system to be nutrient limited and relatively unaffected by forecast climate change, especially in the benthos. The stability of an Ecosim formulation for large higher tropic level food webs is discussed and it is concluded that this kind of coupled model formulation is better for examining the effects of long-term environmental change than short-term perturbations