A Caltech Library Service

On the Reduction of Errors in DNA Computation

Roweis, Sam and Winfree, Erik (1999) On the Reduction of Errors in DNA Computation. Journal of Computational Biology, 6 (1). pp. 65-75. ISSN 1066-5277. doi:10.1089/cmb.1999.6.65.

PDF - Published Version
See Usage Policy.


Use this Persistent URL to link to this item:


In this paper, we discuss techniques for reducing errors in DNA computation. We investigate several methods for achieving acceptable overall error rates for a computation using basic operations that are error prone. We analyze a single essential biotechnology, sequence-specific separation, and show that separation errors theoretically can be reduced to tolerable levels by invoking a tradeoff between time, space, and error rates at the level of algorithm design. These tradeoffs do not depend upon improvement of the underlying biotechnology which implements the separation step. We outline several specific ways in which error reduction can be done and present numerical calculations of their performance.

Item Type:Article
Related URLs:
URLURL TypeDescription
Winfree, Erik0000-0002-5899-7523
Additional Information:© 1999 Mary Ann Liebert, Inc. Received for publication November 9, 1997; accepted as revised December 13, 1998. We would like to express our appreciation to Professor John Baldeschwieler for his contributions to this paper through early discussions of this work. We are also grateful to our advisor, Professor John Hopfield, for his perpetual wisdom and long-term advice. A preliminary version of this paper previously appeared as Section 5 of Roweis et at. (1998a). The MATLAB code used to generate all the figures in this paper is also available by request from S.R. is supported in part by the Center for Neuromorphic Systems Engineering as a part of the National Science Foundation Engineering Research Center Program under grant EEC-9402726 and by the Natural Sciences and Engineering Research Council of Canada. E.W. is supported in part by National Institute for Mental Health (NIMH) training grant no. 5 T32 MH 19l38-06 and also by General Motors' Technology Research Partnership program.
Funding AgencyGrant Number
NSF Engineering Research Center ProgramEEC-9402726
Natural Sciences and Engineering Research Council of CanadaUNSPECIFIED
National Institute for Mental Health (NIMH)5 T32 MH 19l38-06
General Motors' Technology Research Partnership ProgramUNSPECIFIED
Subject Keywords:DNA computations; error reduction; errors; molecular computation
Issue or Number:1
Record Number:CaltechAUTHORS:20110309-104205331
Persistent URL:
Official Citation:SAM ROWEIS, ERIK WINFREE. Journal of Computational Biology. Spring 1999, 6(1): 65-75. doi:10.1089/cmb.1999.6.65
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:22778
Deposited By: Lucinda Acosta
Deposited On:10 Mar 2011 16:05
Last Modified:09 Nov 2021 16:08

Repository Staff Only: item control page