Biomolecular computing: Is it ready to take off?

Fu, Pengcheng

doi:10.1002/biot.200600134

Cited by 19 publications

(11 citation statements)

References 74 publications

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“…[31,32] For networks of more than order 10 binary steps, additional non-binary network elements, as well as proper network design to utilize redundancy for digital error correction, will be needed for fault-tolerant operation. [10,12,17,30] The level of noise in the environments envisaged for applications of future chemical [1][2][3][4] and biomolecular [5][6][7][8][9][10][11][12]14,17,[19][20][31][32][33][34] computing systems is quite high as compared to the electronic computer counterparts. Indeed, both the input/output signals and the "gate machinery" chemical concentrations, can typically fluctuate several percent or more, on the scale normalized to the digital 0 to 1 range.…”

Section: Introductionmentioning

confidence: 99%

Control of Noise in Chemical and Biochemical Information Processing

Privman

2011

Israel Journal of Chemistry

103

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Abstract:We review models and approaches for error-control in order to prevent the buildup of noise when gates for digital chemical and biomolecular computing based on (bio)chemical reaction processes are utilized to realize stable, scalable networks for information processing.Solvable rate-equation models illustrate several recently developed methodologies for gatefunction optimization. We also survey future challenges and possible new research avenues.

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Section: Introductionmentioning

confidence: 99%

Control of Noise in Chemical and Biochemical Information Processing

Privman

2011

Israel Journal of Chemistry

103

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“…Biocomputers. The idea of a biocomputer was first suggested by Feynman in 1959, and theoretically discussed through the eighties and beginning of the 1990s [54], for example in the visionary paper by Michael Conrad,"On design principles for a molecular computer" [33]. It was argued that the natural concurrency present in biocomputing could be used to solve difficult combinatorial problems, e.g., NP-complete problems.…”

Section: Wang Tilesmentioning

confidence: 99%

“…The advantage of such a "biocomputer" is potentially massive parallelism: the theoretical ability of DNA to contain data is 10 21 bits per gram, and the energy requirement is low: 2 * 10 19 operations are theoretically possible per joule [54]. Lipton found theoretical methods for solving NP-complete problems in general using DNA computers [82], and several enhancements were provided, e.g.…”

Section: Wang Tilesmentioning

confidence: 99%

“…Adleman made a groundbreaking proof of concept in 1994: a DNA based computer that solved an instance of a special case of the traveling salesman problem with 7 cities [1]. Several other possible advantages of a biocomputer were theorized-including biology-inspired properties such as autonomy, self-assembly, self-repair, high information density [57,54], and advantages due to inherent parallellism:In a world where parallel computing is in focus, molecular interactions like communication over noisy media and load balancing are inherent in the structure of molecules refined by evolution.Garzon and Deaton, [57] As many different molecules can be synthesized at low cost and exist abundantly around us [57], natural resources are plentifully available for biocomputation. Another great potential lies in the fact that a biocomputer can in principle interact directly with other biological material, including the cells in the human body [11].…”

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confidence: 99%

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Computational Biology: A Programming Perspective

Hartmann

Jones

Simonsen

et al. 2011

Formal Modeling: Actors, Open Systems, Biological Systems

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Abstract. Computation via biological devices has been the subject of close scrutiny since von Neumann's early work some 60 years ago. In spite of the many relevant works in this field, the notion of programming biological devices seems to be, at best, ill-defined. While many devices are claimed or proved to be computationally universal in some sense, the full step to a bona fide programming language is rarely taken, and one question is noticeable by its absence: If the device is universal, where are the programs?We begin with an extensive review of the literature on programmingrelated biocomputing; and briefly identify some strengths and shortcomings from a programming perspective. To show concretely what one could see as programming in biocomputing, we outline (from recent work) a computation model and a small programming language that are biologically more plausible than existing silicon-inspired models. Whether or not the model is biologically plausible in an absolute sense, we believe it sets a standard for a biological device that can be both universal and programmable. ContextThe terms "biocomputing" and "systems biology", taken in their broadest senses, span many fields and areas of research: biology, chemistry, physics, mathematics, electrical engineering and computer science among others. Two major subareas:-Computer modeling of biological and biomolecular processes -Biological hardware for computationThe terms "biomolecular computation" and "biomolecular computational model" occur with both meanings in the literature (see Section 4), sometimes referring to the one and sometimes the other subarea. This paper emphasises the second. More precisely: we take a synthetic viewpoint, concerned with building things as in the engineering and computer sciences. This is in contrast to the inevitable and ubiquitous analytic viewpoint common to the natural sciences, concerned with finding out how naturally evolved things work. We ask: What can be done or built or constructed; and not: how does nature work? (Caveat: just as in engineering, one will need to understand nature's cause-and-effect sufficiently well to be able to modulate it, i.e., to use nature to effectively serve our purposes.) A Theme: Biological Problem-SolvingOur main aim is thus to use the biological world as a computational medium. From a programming perspective, the main goal is problem-solving by writing programs. This section thus refers to solving problems by biology, not solving problems about biology or in biology.Given: a computational problem. To find: a biological solution. Further, problem-solving by a program means finding a general solution (and not just one run of one algorithm on one input data instance).A top-down approach is to devise a model of computation that -satisfies requirements for computer science/engineering -that could conceivably be realised in a biological medium -in which programs are clearly visible, and programming can be done -is a framework in which it is possible, at least in principle, to say when a problem has be...

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“…Despite significant advances in DNA-based computing [12][13][14], examples of enzyme-based computing are sparse, but the inherent advantage that enzymes exhibit over DNA is catalytic specificity. To date, enzyme-based logic gates using chemical inputs have been demonstrated for XOR, INHIBIT A, INHIBIT B, AND, OR, NOR, Identity, and Inverter Boolean operators [15,16].…”

Section: Introductionmentioning

confidence: 99%

Information Security Applications Based on Biomolecular Systems

Strack

Luckarift

Johnson³

et al. 2012

Biomolecular Information Processing

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IntroductionModern computers rely on networked logic gates performing Boolean operations to carry out binary computational functions. By extending the same digital paradigms to molecular [1][2][3][4] and biomolecular computing systems [5,6], chemical processes can mimic electronic counterparts and perform logic operations. For example, Boolean logic gates such as AND, OR, XOR, NOR, NAND, and INHIB, have been demonstrated based on switchable molecular systems [1][2][3][4]. In addition, a wide range of biomolecules have been used for information processing [5,6]. The simplicity of biomolecular processing is attributed to the inherent substrate specificity and versatility of biomolecules; thus the application of biomolecular systems for processing chemical and biochemical information has reached high levels of complexity, despite employing only simple chemical signals.Compared to the advanced power and complexity of computing performed in silico, molecular and biomolecular computing is primitive; however, biomolecular information processing has a niche application in small portable devices that rely on a specific bioelectronic interface. In this area of technological development, portable biomedical sensors [7] with built-in diagnostic capabilities and controlled by simple biomolecular logic operations can be realized [8][9][10][11].Despite significant advances in DNA-based computing [12][13][14], examples of enzyme-based computing are sparse, but the inherent advantage that enzymes exhibit over DNA is catalytic specificity. To date, enzyme-based logic gates using chemical inputs have been demonstrated for XOR, INHIBIT A, INHIBIT B, AND, OR, NOR, Identity, and Inverter Boolean operators [15,16]. These single logic gates all operate as independent systems, that is, the output does not act as an input for a subsequent logic operation. In contrast, biocatalytic logic systems with increased complexity can be designed by defining specific reaction cascades [17]. In fact, biocatalytic cascades found in Nature provide insight into engineering such systems. Thus, by combining enzymes with interconnected and compatible reactions, Baron et al. [16] have demonstrated half-adder and Biomolecular Information Processing: From Logic Systems to Smart Sensors and Actuators, First Edition. Edited by Evgeny Katz.

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Biomolecular computing: Is it ready to take off?

Cited by 19 publications

References 74 publications

Control of Noise in Chemical and Biochemical Information Processing

Control of Noise in Chemical and Biochemical Information Processing

Computational Biology: A Programming Perspective

Information Security Applications Based on Biomolecular Systems

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