Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the computational dynamics of the prokaryotic ‘two component system’ protein network (original) (raw)
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Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2012
Computers since the 1940s have shared the same basic architecture described by Turing and von Neumann, in which one central processor has access to one contiguous block of main memory. This architecture is challenged by modern applications that require greater parallelism, distribution, coordination, and complexity. Here we show that a model of protein interactions can serve as a new architecture, performing useful calculations in a way that provides for much greater scalability, flexibility, adaptation, and power than does the traditional von Neumann architecture. We found that even this simple simulation of protein interactions is universal, being able to replicate the calculation performed on a digital computer, yet without relying upon a central processor or main memory. We anticipate that the convergence of information-and life-sciences is poised to deliver a platform that invigorates computing as it provides insight into the complexity of living systems.
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Proteins: Structure, Function, and Bioinformatics, 2006
Can proteins be used as computational devices to address difficult computational problems? In recent years there has been much interest in biological computing, that is, building a general purpose computer from biological molecules. Most of the current efforts are based on DNA because of its ability to self-hybridize. The exquisite selectivity and specificity of complex protein-based networks motivated us to suggest that similar principles can be used to devise biological systems that will be able to directly implement any logical circuit as a parallel asynchronous computation. Such devices, powered by ATP molecules, would be able to perform, for medical applications, digital computation with natural interface to biological input conditions. We discuss how to design protein molecules that would serve as the basic computational element by functioning as a NAND logical gate, utilizing DNA tags for recognition, and phosphorylation and exonuclease reactions for information processing. A solution of these elements could carry out effective computation. Finally, the model and its robustness to errors were tested in a computer simulation.
Modelling Bacterial Signal Transduction Pathways through Evolving Artificial Chemistries
This paper describes how signal transduction pathways (STP) can be modelled as a rule-based articial chemistry (AC). Articial chemistries provide a powerful operating system where arbitrary STPs can be implemented. A bacteria simulator allowing user controlled ex- periments has been created so that dieren t rule sets and environmental settings can be tested and evolved. Each bacterium contains concentra- tions of user dened modules which interact each time step according to user specied rules and environmental conditions. Modules can encode for operons, proteins and complexes, enabling the simulation of numer- ous biological scenarios. Three distinct experiments undertaken with the bacteria simulator are presented in this paper. In the rst study, we in- vestigate our model of chemotaxis in E. coli where realistic adaptations of tumbling frequencies are observed as well as realistic reactions to en- vironmental change. In a second study, bacteria inherit a colour gene and their evolv...
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Molecular computation models: unconventional approaches
Biology has long inspired unconventional models of computations to computer scientists. In this paper, we will focus on a model inspired by biological development both at the molecular and cellular levels. Such biological processes are particularly interesting for computer science because the dynamic organization emerges from many decentralized and local interactions that occur concurrently at several time and space scales. Thus, they provide a source of inspiration to solve various problems related to mobility, distributed systems, open systems, etc.
Modelling Bacterial Signal Transduction Pathways through Evolving Artifical Chemistries
2003
This paper describes how signal transduction pathways (STP) can be modelled as a rule-based artificial chemistry (AC). Artificial chemistries provide a powerful operating system where arbitrary STPs can be implemented. A bacteria simulator allowing user controlled experiments has been created so that different rule sets and environmental settings can be tested and evolved. Each bacterium contains concentrations of user defined modules which interact each time step according to user specified rules and environmental conditions. Modules can encode for operons, proteins and complexes, enabling the simulation of numerous biological scenarios. Three distinct experiments undertaken with the bacteria simulator are presented in this paper. In the first study, we investigate our model of chemotaxis in E. coli where realistic adaptations of tumbling frequencies are observed as well as realistic reactions to environmental change. In a second study, bacteria inherit a colour gene and their evolving inheritance patterns are visualized. Finally, each bacterium is encoded on a DNA-like genome which is interpreted to specify the gene binding sites and protein production rules. Protein and gene compounds interact in an AC, producing STPs that control observable behaviours such as moving, splitting and eating. Through genome inheritance and mutation, a virtual bacteria culture is evolved.
Biomolecular computing—a shape of computation to come
SIGACT News, 1997
1 Introduction Biomolecular computing is the computing methodology in which biologically important molecules are used as memory. The'aperiodic'nature of these polymeric molecules makes them suitable as memory units [GRY56, WHR+ 87]. Instead of monotonous repeating units of most synthetic polymers (such as polyethylene), certain biological polymers (such as DN A, RN A and protein) ha ve sets of repeating (or information encoding) units, and these units can appear in any order. The use of atomic or molecular- ...
Information processing in biological molecular machines
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Molecular Computing with Artificial Neurons
2000
Abstract—Today’s computers are built up from a minimal set of standard pattern recognition opera- tions. Logic gates, such as NAND, are common ex- amples. Biomolecular materials offer an alternative approach, both in terms of variety and context sensi- tivity. Enzymes, the basic switching elements in bio- logical cells, are notable for their ability to discrimi- nate specific molecules in a
Biomolecular computing and programming
IEEE Transactions on Evolutionary Computation, 1999
Molecular computing is a discipline that aims at harnessing individual molecules at nanoscales for computational purposes. The best-studied molecules for this purpose to date have been DNA and bacteriorhodopsin. Biomolecular computing allows one to realistically entertain, for the first time in history, the possibility of exploiting the massive parallelism at nanoscales inherent in natural phenomena to solve computational problems. The implementation of evolutionary algorithms in biomolecules would bring full circle the biological analogy and present an attractive alternative to meet large demands for computational power. This paper presents a review of the most important advances in biomolecular computing in the last few years. Major achievements to date are outlined, both experimental and theoretical, and major potential advances and challenges for practitioners in the foreseeable future are identified. A list of sources and major events in the field has been compiled in the Appendix, although no exhaustive survey of the expanding literature is intended.