A design for DNA computation of the OneMax problem

Abstract Elements of evolutionary computation and molecular biology are combined to design a DNA evolutionary computation. The traditional test problem for evolutionary computation, OneMax problem is addressed. The key feature is the physical separation of DNA strands consistent with OneMax “fitness.”

[1]  D. Wood,et al.  Computation with biomolecules. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[2]  L. Gold,et al.  Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. , 1990, Science.

[3]  Kalyanmoy Deb,et al.  Genetic Algorithms, Noise, and the Sizing of Populations , 1992, Complex Syst..

[4]  J W Szostak,et al.  In vitro genetics. , 1992, Trends in biochemical sciences.

[5]  Walter Cedeño,et al.  In vitro selection for a OneMax DNA evolutionary computation , 1999, DNA Based Computers.

[6]  L M Adleman,et al.  Molecular computation of solutions to combinatorial problems. , 1994, Science.

[7]  Thomas Pellizzari,et al.  Non-Standard Computation , 1997 .

[8]  David E. Goldberg,et al.  Genetic Algorithms, Selection Schemes, and the Varying Effects of Noise , 1996, Evolutionary Computation.

[9]  Andrew D. Ellington,et al.  genetic analysis: Selection and amplification of rare functional nucleic acids , 1991 .

[10]  D. Wood,et al.  DNA Computing Implementing Genetic Algorithms , 1999 .

[11]  Joerg joke Heitkoetter,et al.  The hitch-hiker''s guide to evolutionary computation , 2001 .

[12]  James P. Crutchfield,et al.  Statistical Dynamics of the Royal Road Genetic Algorithm , 1999, Theor. Comput. Sci..

[13]  S. Grimwade.  Recombinant DNA , 1977, Nature.

[14]  R. Deaton,et al.  A DNA based implementation of an evolutionary search for good encodings for DNA computation , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[15]  Jeffrey Horn,et al.  Handbook of evolutionary computation , 1997 .

[16]  W. Langdon,et al.  Analysis of Schema Variance and Short Term Extinction Likelihoods , 2001 .

[17]  M. Vose.  The Simple Genetic Algorithm , 1999 .

[18]  Gerald F. Joyce,et al.  Selection in vitro of an RNA enzyme that specifically cleaves single-stranded DNA , 1990, Nature.

[19]  W. Stemmer.  DNA shuffling by random fragmentation and reassembly: in vitro recombination for molecular evolution. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Philippe Giguere.  Population Sizing for Optimum Sampling with Genetic Algorithms: A Case Study of the Onemax Problem , 1998 .

[21]  Zbigniew Michalewicz,et al.  Handbook of Evolutionary Computation , 1997 .

[22]  J. Bram,et al.  Encyclopedia of molecular biology and molecular medicine , 1997 .

[23]  Carlo C. Maley,et al.  DNA Computation: Theory, Practice, and Prospects , 1998, Evolutionary Computation.

[24]  J. Crutchfield,et al.  The Evolutionary Unfolding of Complexity , 1999, adap-org/9903001.

[25]  R. Pool.  FORGET SILICON, TRY DNA COVER STORY , 1996 .

[26]  Alan Dove,et al.  From bits to bases: Computing with DNA , 1998, Nature Biotechnology.

[27]  E. Grinfeld,et al.  Searching for gene defects by denaturing gradient gel electrophoresis. , 1986, Cold Spring Harbor symposia on quantitative biology.

[28]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[29]  W. Stemmer.  The Evolution of Molecular Computation , 1995, Science.

[30]  W. Stemmer.  Rapid evolution of a protein in vitro by DNA shuffling , 1994, Nature.

[31]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[32]  Thomas Bäck,et al.  Evolutionary Computation as a Paradigm for DNA-Based Computing , 2002 .

[33]  H. Thiesen,et al.  Target Detection Assay (TDA): a versatile procedure to determine DNA binding sites as demonstrated on SP1 protein. , 1990, Nucleic acids research.

[34]  L. Adleman.  Computing with DNA , 1998 .

[35]  D. Goldberg,et al.  Signal, noise, and genetic algorithms , 1991 .