Molecules That Make Decisions

Credi, Alberto

doi:10.1002/anie.200700879

Cited by 296 publications

(150 citation statements)

References 44 publications

Supporting

Mentioning

148

Contrasting

Order By: Relevance

“…This difficulty [10,12,19] is shared by most, but especially catalytic, (bio)chemical computing gates and can be traced to that "activities" of reagents and catalysts are effectively cancelled out in the leading, linear order in defining the rescaled "logic-range" variables, see Equations (5)- (6). Finally, we note that both variables in Figure 2 need not be limited to [0,1]; the curves are well-defined and shown for x and z larger than 1 as well.…”

Section: From (Bio)chemical Information Processing Gates To Networkmentioning

confidence: 99%

“…[18][19][20] Reported results for networks [1][2][3][4][18][19][20] of (bio)chemical information processing units have included systems performing elements of basic arithmetic operations, [21][22] multifunctional molecules, [23][24][25] DNAbased gates and circuits, [26,27] and enzyme-catalyzed reactions realizing concatenated gates. [19,20,28,29] Here we introduce, by illustrative model examples, concepts in noise reduction and control for scalability in biochemical computing.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, chemical processes can be cast [35,36] in the language of computing operations, with signals represented by changes [1][2][3][4][36][37][38][39][40][41][42][43][44][45][46][47][48] in structural, chemical, or physical properties, resulting due to physical, chemical, [77][78][79][80][81][82][83][84] or more than one type [53,[85][86][87] of input. The output signals can be detected spectroscopically [88][89][90][91][92][93] or electrically/electrochemically.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Control of Noise in Chemical and Biochemical Information Processing

Privman

2011

Israel Journal of Chemistry

103

View full text Add to dashboard Cite

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.

show abstract

Section: From (Bio)chemical Information Processing Gates To Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Control of Noise in Chemical and Biochemical Information Processing

Privman

2011

Israel Journal of Chemistry

103

View full text Add to dashboard Cite

show abstract

“…These developments have been motivated by interest in information and signal processing of the "digital" nature, by utilizing chemical [1][2][3][4][5] and biochemical [6][7][8][9][10] information processing, including that based on enzymatic processes. 11,12 Many of the studied designs have aimed at mimicking binary logic gate functions, [13][14][15] arithmetic operations, 16 and generally Boolean logic circuits.…”

Section: Introductionmentioning

confidence: 99%

Extended Linear Response for Bioanalytical Applications Using Multiple Enzymes

2013

View full text Add to dashboard Cite

We develop a framework for optimizing a novel approach to extending the linear range of bioanalytical systems and biosensors by utilizing two enzymes with different kinetic responses to the input chemical as their substrate. Data for the flow-injection amperometric system devised for detection of lysine based on the function of L-Lysine-alpha-Oxidase and Lysine-2-monooxygenase are analyzed. Lysine is a homotropic substrate for the latter enzyme. We elucidate the mechanism for extending the linear response range and develop optimization techniques for future applications of such systems.

show abstract

“…Biochemical processes, 1-8 and more generally, chemical kinetics, [9][10][11][12][13][14][15] Presently, biochemical information processing systems are not intended as a replacement of Si devices, but rather aim at offering additional functionalities in situations where direct wiring to computers and power sources is not practical such as in many biomedical applications. [23][24][25] However, even for near-term applications, scalable and versatile networking paradigms are crucial.…”

Section: Introductionmentioning

confidence: 99%

Biochemical Filter with Sigmoidal Response: Increasing the Complexity of Biomolecular Logic

et al. 2010

View full text Add to dashboard Cite

The first realization of a designed, rather than natural, biochemical filter process is reported and analyzed as a promising network component for increasing the complexity of biomolecular logic systems. Key challenge in biochemical logic research has been achieving scalability for complex network designs. Various logic gates have been realized, but a "toolbox" of analog elements for interconnectivity and signal processing has remained elusive. Filters are important as network elements that allow control of noise in signal transmission and conversion. We report a versatile biochemical filtering mechanism designed to have sigmoidal response in combination with signal-conversion process. Horseradish peroxidase-catalyzed oxidation of chromogenic electron donor by H 2 O 2 , was altered by adding ascorbate, allowing to selectively suppress the output signal, modifying the response from convex to sigmoidal. A kinetic model was developed for evaluation of the quality of filtering. The results offer improved capabilities for design of scalable biomolecular information processing systems.Web-link to future updates of this article: www.clarkson.edu/Privman/231.pdf 600-2 - IntroductionBiochemical processes, 1-8 and more generally, chemical kinetics, [9][10][11][12][13][14][15] Presently, biochemical information processing systems are not intended as a replacement of Si devices, but rather aim at offering additional functionalities in situations where direct wiring to computers and power sources is not practical such as in many biomedical applications. [23][24][25] However, even for near-term applications, scalable and versatile networking paradigms are crucial. Recent studies suggest 8,58,59 that the level of noise in biochemical systems is quite high as compared to electronics. This includes noise both the input/output signals and in the "gate machinery" chemical (e.g., enzyme) concentrations. Avoiding noise amplification by appropriate network design is therefore quite important even for small networks, similar to recent findings 60 for networking of neurons. Present estimates 8,61 suggest that, not only analog but also digital error correction will be required for networks involving more than order 10 processing steps.-3 -Considerations of scalability and control of noise have set the stage for new challenges.Large-scale interconnectivity and fault-tolerance cannot be achieved without the development of a "toolbox" of new network elements including filters, signal splitters, signal balancers, resetting functions, etc. These analog network elements for biochemical computing might not follow too closely the device components of Si electronics. In fact, concepts borrowed from natural systems, specifically, memory involving processes 62 have recently received attention in unconventional information processing studies. However, as a rule none of the standard elements for networking for (ultimately, digital) information processing has been experimentally realized to date in a setting demonstrating interconnectivity ...

show abstract

Molecules That Make Decisions

Cited by 296 publications

References 44 publications

Control of Noise in Chemical and Biochemical Information Processing

Control of Noise in Chemical and Biochemical Information Processing

Extended Linear Response for Bioanalytical Applications Using Multiple Enzymes

Biochemical Filter with Sigmoidal Response: Increasing the Complexity of Biomolecular Logic

Contact Info

Product

Resources

About