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

The chaotic nature of healthcare information systems: The need for transdisciplinary collaboration

Copyright @ 2013 EMCIS.This paper demonstrates one of the challenges of the healthcare information systems development, namely the chaotic nature of healthcare systems. Although the reliable evidence demonstrating the positive effects of health information systems on safety and quality remains inconclusive (a growing body of research revealing the unintended consequences and potentially error producing effects of health information systems’ implementation. Different arguments from the literature concerning the chaotic nature of healthcare, including but not limited to the nature of patients and disease have been presented. The requirements of new ways of systems design and the need for transdisciplinary dynamic teams within the requirements engineering phase as a start has been discussed. These arguments have been investigated in the context of an exploratory case addressing one of the advanced oncology centres in the US. This paper concludes that there is an important need to rethink healthcare information systems development method, which has to be in a dynamic ongoing manner for some major issues

Building capacity for evidence-based public health: Reconciling the pulls of practice and the push of research

Timely implementation of principles of evidence-based public health (EBPH) is critical for bridging the gap between discovery of new knowledge and its application. Public health organizations need sufficient capacity (the availability of resources, structures, and workforce to plan, deliver, and evaluate the preventive dose of an evidence-based intervention) to move science to practice. We review principles of EBPH, the importance of capacity building to advance evidence-based approaches, promising approaches for capacity building, and future areas for research and practice. Although there is general agreement among practitioners and scientists on the importance of EBPH, there is less clarity on the definition of evidence, how to find it, and how, when, and where to use it. Capacity for EBPH is needed among both individuals and organizations. Capacity can be strengthened via training, use of tools, technical assistance, assessment and feedback, peer networking, and incentives. Modest investments in EBPH capacity building will foster more effective public health practice

The Local Emergence and Global Diffusion of Research Technologies: An Exploration of Patterns of Network Formation

Grasping the fruits of "emerging technologies" is an objective of many government priority programs in a knowledge-based and globalizing economy. We use the publication records (in the Science Citation Index) of two emerging technologies to study the mechanisms of diffusion in the case of two innovation trajectories: small interference RNA (siRNA) and nano-crystalline solar cells (NCSC). Methods for analyzing and visualizing geographical and cognitive diffusion are specified as indicators of different dynamics. Geographical diffusion is illustrated with overlays to Google Maps; cognitive diffusion is mapped using an overlay to a map based on the ISI Subject Categories. The evolving geographical networks show both preferential attachment and small-world characteristics. The strength of preferential attachment decreases over time, while the network evolves into an oligopolistic control structure with small-world characteristics. The transition from disciplinary-oriented ("mode-1") to transfer-oriented ("mode-2") research is suggested as the crucial difference in explaining the different rates of diffusion between siRNA and NCSC