Within the Natural Computing Group GCN we address two working perspectives: on the one hand, we propose new bioinspired computational models and architectures, and on the other, we propose computational techniques and user friendly tools to support the advancements in synthetic and systems biology. An in-depth reflection on the distinctive nature of biological information is necessary in both directions; our group has actually established several research lines and projects in the “informational” confluence of the two working perspectives.
From the point of view of the bioinspired computational models we intend to develop mathematical and computational models abstracted from the information processing that is present in all living cellular systems. The emphasis is at the cellular level; and the modelling methods capture the internal structure of the cell and the cellular interactions in an appropriate way such that they allow for the description of what are essentially massively parallel computational systems. We study the problem solving capabilities inherent in the living cell, which are realized by maintaining a special, “meaningful” relationship with the internal/external environment, integrating the self-reproduction processes within the information flow of incoming and outgoing signals. The designs encoded by natural systems are optimized by evolution to provide solutions to physical problems posed by both individual development and continued viability across many environments and evolution.
From a computational point of view, the living cell may be viewed as a DNA-based molecular computer, endowed with an enzyme-protein operating system, which is coded into the DNA memory bank. We are attracted by the new possibilities for computing offered by these self-organizing, interlinked, and evolvable molecular systems: practically an unbound memory and a huge parallelism which might be used for solving intractable problems in a reasonable time. Furthermore, these molecules participate in very complex networks in cellular subsystems, including regulatory networks for gene expression, intracellular metabolic networks, and both intra- and intercellular communication networks. Subsequently the new biocomputing ideas extracted from these core subsystems have potential to be applied not only to biological-cellular instances, but also to modelling of interactive, self-organizing processes in many other fields: population interactions, ecological trophic networks, industrial ecosystems and companies, virtual economies, social and cultural dynamics, etc. We are sure the results derived from the advancement of the bioinformational research program will open new avenues for information science and technology, and will be conducive to a paradigm shift in the way bioinspired technologies are conceived and applied.
From the point of view of the computational techniques and tools to support synthetic and systems biology, we pretend the realization of simulations and tools that are user-friendly and can support the study, analysis, and extraction of further information in an intelligent and meaningful way. Both molecular dynamics and cellular systemic interactions will be considereded. In regard to molecular dynamics, we specifically attempt an analysis of the prion propagation and the protein aggregation phenomena (based on altered processes of molecular recognition) with the aim of helping researchers in their studies about the detection and treatment of neurodegenerative disorders. With regard to cell systems interaction we attempt a consistent approach to the multiple varieties of information in the living cell, also by starting out from the conceptualization of molecular recognition phenomena. Subsequently, an elementary approach to the “informational architectures” behind cellular complexity may be chartered. In the interplay of the different informational architectures, two crucial cellular subsystems should be highlighted: on the one side the transcriptional regulatory network, and on the other, the cellular signalling system that is in charge of the interrelationship with the environment and how the topological governing of this network is deployed by the cellular signalling system in charge of the interrelationship with the environment. Models and simulations of this basic interaction will be applied to Mycobacterium tuberculosis signalling in living tissues (in cooperation with an ongoing research medical project). More generally, as suggested above, the embodiment of functional protein agents and the peculiar handling of DNA sequences along the evolutionary process will suggest a parallel with the von Neumann scheme of modern computers, including the cellular capability to “rewrite the DNA rules” along ontogenetic development. In these theoretical and applied research areas we collaborate with Biomolecular Research Groups in the Complutense University and Biological Research Center of Madrid, and with the Bioinformation Group of the Aragon Institute of Health Sciences of Spain, respectively.
Fernando Arroyo Montoro
Universidad Politécnica de Madrid, Spain