Gene expression and fast construction of distributed evolutionary representation

The gene expression process in nature produces different proteins in differ ent cells from different portions of the DNA. Since proteins control almost every important activity in a living organism, at an abstract level, gene expression can be viewed as a process that evaluates the merit or "fitness" of the DNA. This distributed evaluation of the DNA would not be possible w ithout a decomposed representation of the fitness function defined over the DNAs. This paper argues that, unless the living body was provided with suc h a representation, we have every reason to believe that it must have an ef ficient mechanism to construct this distributed representation. This paper demonstrates Polynomial-time computability of such a representation by prop osing a class of efficient algorithms, The main contribution of this paper is two-fold. On the algorithmic side, it offers a way to scale up evolution ary search by detecting the underlying structure of the search space. On th e biological side, it proves that the distributed representation of the evo lutionary fitness function in gene expression can be computed in polynomial -time. It advances our understanding about the representation construction mi gene expression from the perspective of computing. It also presents expe rimental results supporting the theoretical performance of the proposed alg orithms.