Multi-science decision support for HIV drug resistance treatment

The complete cascade from genome, proteome, metabolome, and physiome, to health forms multiscale, multiscience systems and crosses many orders of magnitude in temporal and spatial scales. The interactions between these systems create exquisite multitiered networks, with each component in nonlinear contact with many interaction partners. Understanding, quantifying, and handling this complexity is one of the biggest scientific challenges of our time. In this paper we argue that computer science in general, and Grid computing in particular, provide the language needed to study and understand these systems, and discuss a case study in decision support for HIV drug resistance treatment within the European ViroLab project.