Model organisms are a living form of scientific models. Despite the widespread use of model organisms in scientific research, the actual representational relationship between model organisms and their target species is often poorly characterized in the context of cross-species research. Many model organisms do not represent the target species adequately, let alone accurately. This is partly due to the complex and emergent life phenomena in the organism, and partly due to the fact that a model organism is always taken to (...) represent a broad range of diverse organisms. More often than not, model organisms are taken as a reference point for an extrapolation to be made to the unknown characteristics of other species. I propose to view model organisms as analogue simulators which represent the emergent phenomenon in the context of cross-species research. A model organism represents a wide range of species by simulating their molecular microstates which underlie various emergent phenomena. I show that although model organisms represent the target species inadequately at many levels of complexity, they have epistemic values as a simulator in virtue of which the emergent phenomenon can be modeled dynamically, a virtue that is hardly attainable by non-dynamic models. (shrink)

The different kinds of knowledge which were connected in Natural Philosophy (NP) have been later separated. The real separation came when Physics took its individuality and developed specific mathematical models, such as dynamic systems. These models are not adapted to an integral study of _living systems_, by which we mean evolutionary multi-level, multi-agent, and multi-temporality self-organized systems, such as biological, social, or cognitive systems. For them, the physical models can only be applied to the local dynamic of each co-regulator agent, (...) but not to the global dynamic intertwining these partial dynamics. To ‘revive’ NP, we present the Memory Evolutive Systems (MES) methodology which is based on a ‘dynamic’ Category Theory; it proposes an info-computational model for living systems. Among the main results: (i) a mathematical translation of the part⁻whole problem (using the categorical operation colimit) which shows how the different interpretations of the problem support diverging philosophical positions, from reductionism to emergentism and holism; (ii) an explanation of the emergence, over time, of structures and processes of increasing complexity order, through successive ‘complexification processes’. We conclude that MES provides an emergentist-reductionism model and we discuss the different meanings of the concept of _emergence_ depending on the context and the observer, as well as its relations with anticipation and creativity. (shrink)