Abstract
Early biomolecular computing research focussed on laboratoryscale human-operated DNA models of computation for solving complex computational problems. These models generate large combinatorial libraries of DNA to provide search spaces for parallel filtering algorithms. Many difierent methods for library generation, solution filtering, and output generation were experimentally studied. This chapter addresses the basic filtering models and describes two basic computationally complete and universal DNA models of computation, splicing model and sticker model.
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References
Adleman L (1994) Molecular computation of solutions of combinatorial problems. Science 266:1021–1023
Adleman L (1996) On constructing a molecular computer. DIMACS 27:1–21
Amos M(2005) Theoretical and experimental DNA computation. Springer, Berlin Heidelberg
Bach E, Condon A, Glaser E, Tanguay C (1996) DNA models and algorithms for NP-complete problems. Proc 11th Ann IEEE Conf Comp Complex, Philadelphia, 290–299
Braich RS, Chelyapov N, Johnson C, Rothemumd PWK, Adleman L (2002) Solution of a 20-variable 3-sat problem on a DNA computer. Science 296:499– 502
Faulhammer D, Cukras AR, Lipton RJ, Landweber LF (2000) Molecular computation: RNA solutions to chess problems. PNAS 97:1385–1389
FellerW(1968) An introduction to probability theory and its applications. Wiley, New York
Feynman RP (1961) Miniaturization. In: Gilbert DH (ed.). Reinhold, New York
Freund R, Kari L, Pâun G (1999) DNA computing based on splicing: the existence of universal computers. Theory Comp Systems 32:69–112
Gibbons A, Amos M, Hodgson D (1996) Models of DNA computation. LNCS 1113:18–36
Guo M, Chang WL, Ho M, Lu J, Cao J (2005) Is optimal solution of every NPcomplete or NP-hard problem determined from its characteristic for DNA-based computing? Biosystems 80:71–82
Head T (1987) Formal language theory and DNA: an analysis of the generative capacity of specific recombinant behaviors. Bull Math Biol 47:737–759
Henkel CV, Rozenberg G, Spaink H (2005) Application to mismatch detection methods in DNA computing. LNCS 3384:159–168
Lipton RJ (1995) DNA solution of hard combinatorial problems. Science 268: 542–545
Liu Q, Wang L, Frutos AG, Condon AE, Corn RM, Smith LM (2000) A surfacebased approach to DNA computing. Nature 403:175–179
Liu Q, Wang L, Frutos AG, Condon AE, Corn RM, Smith LM (2000) DNA computing on surfaces. Nature 403:175–179
Martinez-Perez I (2007) Biomolecular computing models for graph problems and finite state automata. Ph.D. thesis Hamburg Univ Tech
Ouyang Q, Kaplan PD, Liu S, Libchaber A (1997) DNA solution of the maximal clique problem. Science 278:446–449
Păun G, Rozenberg G, Salomaa A (1998) DNA computing: new computing paradigms. Springer, New York
RheoGene (2005) Market Wire
Roweis S, Winfree E, Burgoyne R, Chelyapov N, Goodman M, Rothemund P, Adleman L (1996) A sticker based architecture for DNA computation. In: Baum EB (ed.) DNA Based Computers 1–27
Rozenberg G, Spaink H (2003) DNA computing by blocking. Theoret Comp Sci 292:653–665
Sakakibara Y, Suyama A (2000) Intelligent DNA chips: logical operation of gene expression proviles on DNA computers. Genome Inform 11:33–42
Scharrenberg O (2007) Programming of stickers machines. Project Work, Hamburg Univ Tech
Zimmermann KH (2002) On applying molecular computation to binary linear codes. IEEE Trans Inform Theory 48:505–510
Zimmermann KH (2002) Efficient DNA sticker algorithms for NP-complete graph problems. Comp Phys Comm 114:297-309
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© 2008 Springer-Verlag US
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Ignatova, Z., Zimmermann, KH., Martínez-Pérez, I. (2008). Non-Autonomous DNA Models. In: DNA Computing Models. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-73637-2_5
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DOI: https://doi.org/10.1007/978-0-387-73637-2_5
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