With the increasing complexity of software systems and their widespread
growth into many aspects of our lives, the need to search for new models,
paradigms, and ultimately, technologies, to manage this problem is evident.
The way nature solves various problems through processes evolving during
billions of years was always an inspiration to many computational paradigms;
on the other hand, the complexity of the problems posed by the investigation
of biological systems challenged the research of new tractable models.
Molecular Computation Models: Unconventional Approaches is looking into new
computational paradigms from both a theoretical perspective which offers a
solid foundation of the models developed, as well as from a modeling angle,
in order to reveal their effectiveness in modeling and simulating, especially
biological systems. Tools and programming concepts and implementation issues
are also discussed in the context of some experiments and comparative studies.
Table Of Contents:
Chapter 1. Membrane Computing: Main Ideas, Basic Results, Applications,
Chapter 2. State Transition Dynamics: Basic Concepts and Molecular Computing
Chapter 3. DNA Computing and Errors: a Computer Science Perspective,
Chapter 4. Networks of Evolutionary Processors: Results and Perspectives,
Chapter 5. Cellular solutions to some numerical NP-complete problems: A
Chapter 6. Modeling developmental processes in MGS,
Chapter 7. Computing Bacterial Evolvability using Individual-based Models,
Chapter 8. On a formal model of T cell and its biological feedback,
Chapter 9. Formal Modelling of the Dynamic Behaviour of Biology-Inspired