Design and Simulation of Self-Organizing Microbial Cellular Automata

This paper discusses the design and implementation of cellular automata based on the alteration of genetic sequences in bacteria. The work is composed of five chapters covering the problem, the system’s design, the software simulation of the system and future issues on the problem. The section covering the problem explores the reasons for this work as well as issues that this work solves. The section covering system design details the modified genetic sequences and the algorithm that these sequences implement. The simulation section describes the layout of an experiment along with the test cases experimented on. Finally, the future work section points out lacking information from the work or possible difficulties this solution reveals

On the Power of DNA-Computing

In [Adl94] Adleman used biological manipulations with DNA strings to solve some instances of the Directed Hamiltonian Path Problem. Lipton [Lip94] showed how to extend this idea to solve any NP problem. We prove that exactly the problems in P NP = \Delta p 2 can be solved in polynomial time using Lipton's model. Various modifications of Lipton 's model, based on other DNA manipulations, are investigated systematically, and it is proved that their computational power in polynomial time can be characterized by one of the complexity classes P, \Delta p 2 , or \Delta p 3 . 1 Introduction In the recent years several new ideas have been developed to use non electronic natural phenomena for real, efficient computation. In classical electronic-based computations the information is stored and modified bitwise by electric and electromagnetic means. It is typical for this kind of computations that the number of steps performed per time unit is huge but the number of processors running in..