LNCS 2950 - Aspects of Molecular Computing (Frontmatter Pages)

Digital Information Encoding on DNA
Max H. Garzon 1 , Kiranchand V. Bobba 1 ,andBryanP.Hyde 2
1 Computer Science, The University of Memphis
Memphis, TN 38152-3240, U.S.A.
{mgarzon, kbobba}@memphis.edu
2 SAIC-Scientific Applications International Corporation
Huntsville, AL 35805, U.S.A.
brian.p.hyde@saic.com
Abstract. Novel approaches to information encoding with DNA are
explored using a new Watson-Crick structure for binary strings more
appropriate to model DNA hybridization. First, a Gibbs energy analysis
of codeword sets is obtained by using a template and extant errorcorrecting
codes. Template-based codes have too low Gibbs energies that
allow cross-hybridization. Second, a new technique is presented to construct
arbitrarily large sets of noncrosshybridizing codewords of high
quality by two major criteria. They have a large minimum number of
mismatches between arbitrary pairs of words and alignments; moreover,
their pairwise Gibbs energies of hybridization remain bounded within a
safe region according to a modified nearest-neighbor model that has been
verified in vitro. The technique is scalable to long strands of up to 150mers,
is in principle implementable in vitro, and may be useful in further
combinatorial analysis of DNA structures. Finally, a novel method to encode
abiotic information in DNA arrays is defined and some preliminary
experimental results are discussed. These new methods can be regarded
as a different implementation of Tom Head’s idea of writing on DNA
molecules [22], although only through hybridization.
1 Introduction
Virtually every application of DNA computing [23,1,17] requires the use of appropriate
sequences to achieve intended hybridizations, reaction products, and
yields. The codeword design problem [4,19,3] requires producing sets of strands
that are likely to bind in desirable hybridizations while minimizing the probability
of erroneous hybridizations that may induce false positive outcomes. A fairly
extensive literature now exists on various aspects and approaches of the problem
(see [4] for a review). Approaches to this problem can be classified as evolutionary
[7,15,9] and conventional design [6,19]. Both types of method require the use
of a measure of the quality of the codewords obtained, through either a fitness
function or a quantifiable measure of successful outcomes in test tubes.
Although some algorithms have been proposed for testing the quality of codeword
sets in terms of being free of secondary structure [4,10], very few methods
have been proposed to systematically produce codes of high enough quality to
N. Jonoska et al. (Eds.): Molecular Computing (Head Festschrift), LNCS 2950, pp. 152–166, 2004.
c○ Springer-Verlag Berlin Heidelberg 2004