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Published online on June 23, 2004, 10.1073/pnas.0400731101
PNAS | July 6, 2004 | vol. 101 | no. 27 | 9960-9965
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Computer Sciences / Biochemistry
Stochastic computing with biomolecular automata

Rivka Adar * {dagger}, Yaakov Benenson * {dagger}, {ddagger}, Gregory Linshiz *, {ddagger}, Amit Rosner §, Naftali Tishby §, ¶, and Ehud Shapiro *, {ddagger}, ||

Departments of *Biological Chemistry and {ddagger}Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel; §School of Computer Science and Engineering and Center for Neural Computation, Hebrew University, Jerusalem 91904, Israel

Edited by Richard M. Karp, International Computer Science Institute, Berkeley, CA, and approved May 5, 2004 (received for review February 2, 2004)

Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure.

This paper was submitted directly (Track II) to the PNAS office.

Freely available online through the PNAS open access option.

Abbreviation: FAM, carboxyfluorescein.

{dagger} R.A. and Y.B. contributed equally to this work.

|| To whom correspondence should be addressed. E-mail: ehud.shapiro{at}weizmann.ac.il.

© 2004 by The National Academy of Sciences of the USA


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