In computational theory, several formal approaches make use of biology as inspiration for the development of problem solving techniques. Most of them are taken from complex, inherently concurrent, systems. Some examples of "biologically inspired computing" are artificial immune systems, cellular automata, genetic algorithms, membrane computing, neural networks, organic computing, swarm intelligence.

On the other hand, concurrency has itself begun to inspire an emerging research area in Biology. Regev and Shapiro coined in 2002 the Cells-as-Computation metaphor as the "much-needed abstraction for biomolecular systems". Computers and biomolecular systems both start from a small set of elementary components from which, layer by layer, more complex entities are constructed with evermore sophisticated functions. In computational systems biology, the abstractions, tools and methods used to specify and study concurrent and distributed systems can therefore be naturally adopted to model and better understand the complex biomolecular systems.

In this workshop we intend to explore this "cross-fertilization" between computational sciences and biology, with a special attention to concurrent models in biology and formal foundations in bio-inspired computing. Concurrency theory permits hypotheses generation and testing. Models can therefore be simulated, analyzed, checked and validated. A growing "arsenal" of theoretical models, logics, and tools for understanding concurrent systems has been developed. We recognize that concurrency permeates not only computer systems but also nature and living organisms. We can find concurrency at the molecular level as well as at those of cells, organs, individuals, communities and ecological systems. Also, biologically inspired computing could benefit from concurrency theory.