Multidisciplinary Investigation into Adult Stem Cell Behavior

We are part of a multi-disciplinary team investigating new understandings of stem cell behaviour, and specifically looking novel ideas about how adult stem cells behave and organise themselves in the human body. We have used different methods and mechanisms for investigating and interpreting these new ideas from medical science. These have included mathematical modelling, simulation and visualisation as well as a series of art pieces that have resulted from looking at the overall nature of our combined multi-disciplinary attempt to investigate new theories of biological organisation. In this paper we look at several issues relating to our project. First, we provide reasons for why formal models and simulations are needed to explore this growing area of research. Is there an argument to suggest that we need simulations as a way in to understanding various properties of stem cells that are observed in wet lab experiments? Next, an introduction on current theoretical models of stem cells is presented along with an outline of some of the problems and limitations of these approaches. We then provide an overview of our agent-based model of stem cells, and discuss strategies for implementing this model as a simulation and its subsequent visualisation. Then we discuss the role of the artist (the second author) in developing our model and simulation and the influence of the artwork/exhibition on the other members in our team. Our premise is that artists can conceptualise scientific theories without the standard discipline-specific constraints, and thereby potentially influence the development of scientific theories, their mathematical formulation; and their associated aesthetics. Finally, we argue that for the field of bioinformatics to move forward in a holistic and cohesive manner more multi-disciplinary efforts such as ours would be of significant benefit to this research area [20]. This paper might be viewed as an advert for the benefits of multi-disciplinary teams in understanding new experimental data in medicine and biology.