Computational formalism inspired by Molecular Biology
Partners: IIT-Academy Iasi (leader), University of Iasi, IeAT
Membrane computing is a new and challenging domain, in continuous development, at the crossroad of computer science, mathematics and biology. Researchers in bio-informatics and systems biology start using more and more the formal models from mathematics and computer science, as well as software simulations derived from these formal models. The general purpose of these studies is to understand better the inter- and intra- cellular processes, as well as the complexity of molecular interactions. Exploiting these radically new ideas and new possibilities in TIC research paths, this project proposes new theoretical researches in the domain of membrane and molecular computing, and, in the same time, new implementations for membrane systems and molecular networks, and their application in describing biological processes. We will also continue the study of cellular metaprogramming (introduced by the members of the team in the world-wide scientific circuit) as a functional and coordonating principle of the cell. Our computing paradigm will justify and will allow to change at run-time the behaviour of the programs. We will study the theoretical limits of the cell’s functioning, imposed by the theory of models limitations. The project will take advantage of advanced mathematical and computer science knowledge in the process of modelling, i.e. algebraic models for the genetic message transmission, new categorical and homological methods from higher dimensional automata, the probabilistic/stochastic aspects, as well as the topological aspects of membrane and molecular systems. We will refine the model of molecular networks, trying to simulate as realistic as it can be possible the biological facts. We will use knowledge and various programming paradigms used in computer networks and communicating systems. Our software implementations could replace certain expensive lab experiments. One of our priorities is to elaborate efficient automata models which can improve, at least theoretical, the genetic message (subject to proper genetic encoding). Those problems are hot and papers on these subjects are published in prestigious and high impact journals. Our goal is to obtain such results.