Biomolecular Computing - Bionanoelectronics: Bioinquiring and Bioinspired Devices - page 189

Chapter 7
Biomolecular Computing

Abstract This chapter focuses on biomolecular computing, emphasizing the
advantages and disadvantages of this computational method. Examples of
biomolecular systems that work as memory or that perform Boolean computation,
self-assembly, and logical computations are given.

Because of the recent technological progress in the semiconductor industry, alter-
natives to electronic computations could be of interest only if (1) the computation
speed increases, which implies parallel computation and/or development of more
efficient computing algorithms, or (2) the heat problem, especially relevant in
miniaturized components, can be alleviated. In this chapter, we will address the
issue of biomolecular computing from this perspective.

7.1 Principles of Biomolecular Computing

Biomolecular computing is an appealing candidate for efficient computation since
information processing and memory are common to all life forms and take place
with great reliability in the world around us. The original incentive for developing
biomolecular computation was the expected parallelism and the potential high-
density storage characteristic of biomolecules. Although biomolecular computing is
a parallel process and, therefore, the computation time increases only polynomially
with the number of variables and not exponentially, as in standard computers, the
number of strands involved in the computation that must be prepared increases
exponentially with the number of variables. This is a disadvantage, which implies
an additional time for preparing the strands, which increases exponentially with the
number of variables, and cannot be avoided since it is caused by the still classical
way in which biomolecular computing works ( Feldkamp and Niemeyer 2006 ).
In fact, biomolecular computing experiences the same exponential scaling of the
solution space as electronic computers. The 200-city traveling salesmen problem