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Gene Expression and Fast Construction of Distributed Evolutionary Representation (2001)
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| Venue: | Evolutionary Computation |
| Citations: | 21 - 0 self |
BibTeX
@ARTICLE{Kargupta01geneexpression,
author = {Hillol Kargupta and Byung-Hoon Park},
title = {Gene Expression and Fast Construction of Distributed Evolutionary Representation},
journal = {Evolutionary Computation},
year = {2001},
volume = {9},
pages = {2001}
}
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Abstract
The gene expression process in nature produces different proteins in different 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 without a decomposed representation of the fitness function defined over the DNAs. This paper argues that, unless the living body was provided with such a representation, we have every reason to believe that it must have an efficient mechanism to construct this distributed representation. This paper demonstrates polynomial-time computability of such a representation by proposing 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 evolutionary search by detecting the underlying structure of the search space. On the biological side, it proves that the distributed representation of the evolutionary fitness function in gene expression can be computed in polynomial-time.
Keyphrases
gene expression distributed evolutionary representation fast construction distributed representation underlying structure different protein decomposed representation evolutionary fitness function important activity search space algorithmic side distributed evaluation different cell evolutionary search polynomial-time computability main contribution living body gene expression process different portion living organism fitness function abstract level efficient mechanism efficient algorithm biological side
