da lunedì 5 Maggio a venerdì 9 Maggio dalle 10 alle 13
Natural Computing is an interdisciplinary research field that investigates human-designed computing inspired by nature as well as computation taking place in nature, i.e., it investigates models, computational techniques, and computational technologies inspired by nature as well as it investigates phenomena/processes taking place in nature in terms of information processing.
One of research areas from the second strand of research is a computational understanding of the functioning of the living cell. We view this functioning in terms of formal processes resulting from interactions between (a huge number of) individual reactions. These interactions are driven by two mechanisms, facilitation and inhibition: reactions may (through their products) facilitate or inhibit each other.
We present a formal framework for the investigation of these interactions. We motivate this
framework by explicitly stating a number of assumptions that hold for processes resulting from these interactions, and we point out that these assumptions are very different from the ones underlying traditional models of computation. We discuss some basic properties of these processes, and demonstrate how
to capture and analyse, in our formal framework, some notions related to cell biology and biochemistry.
Research topics in this framework are motivated by biological considerations as well as by the need to understand the underlying computations. The models we discuss turned out to be novel and attractive from the theory of computation point of view. This is extensively discussed throughout the course.
The course is of a tutorial style and self-contained. In particular, no prior knowledge of biochemistry or cell biology is required.
The course is suited for master and PhD students as well as researchers and faculty members. It is of interest to computer scientists and mathematicians interested in formal models of computation as well as to bioinformaticians, biochemists, and biologists interested in foundational/formal understanding of biological processes.
The presented framework was developed jointly with A.Ehrenfeucht from University of Colorado at Boulder.