This challenge is not due to the lack of sophistication in the the current state-of-the-art of stimuli-responsive nanoparticles, many of which can conceptually function as elementary logic gates. This is mostly due to the lack of scalable architectures that would enable systematic integration and wiring of the gates into a large integrated circuit. Previous approaches are limited to i demonstrating one simple logic operation per test tube or ii relying on complicated enzyme-based molecular circuits in solution.
It should be also noted that modular and scalable aspects are key challenges in DNA computing for practical and widespread use.
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In nature, the cell membrane is analogous to a circuit board, as it organizes a wide range of biological nanostructures e. Most importantly, such biological "computing" processes occur in a massively parallel fashion. Information processing on living cell membranes is a key to how biological systems adapt to changes in external environments. This manuscript reports the development of a nanoparticle-lipid bilayer hybrid-based computing platform termed lipid nanotablet LNT , in which nanoparticles, each programmed with surface chemical ligands DNA in this case , are tethered to a supported lipid bilayer to carry out computation.
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Taking inspirations from parallel computing processes on cellular membranes, we exploited supported lipid bilayers SLBs --synthetic mimics for cell surfaces--as chemical circuit boards to construct nanoparticle circuits. This "nano? We introduced two types of nanoparticles to a lipid bilayer that differ in mobility: mobile Nano-Floaters and immobile Nano-Receptors.
Due to high mobility, floaters actively interact with receptors across space and time, functioning as active units of computation. The nanoparticles are functionalized with specially designed DNA ligands, and the surface ligands render receptor-floater interactions programmable, thereby transforming a pair of receptor and floater into a logic gate. A nanoparticle logic gate takes DNA strands in solution as inputs and generates nanoparticle assembly or disassembly events as outputs.
The nanoparticles and their interactions can be imaged and tracked by dark-field microscopy with single-nanoparticle resolution because of strong and stable scattering signals from plasmonic nanoparticles. Using this approach termed "interface programming" , we first demonstrated that a pair of nanoparticles that is, two nanoparticles on a lipid bilayer can carry out AND, OR, INHIBIT logic operations and take multiple inputs fan-in and generate multiple outputs fan-out. Also, multiple logic gates can be modularly wired with AND or OR logic via floaters, as the mobility of floaters enables the information cascade among several nanoparticle logic gates.
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We termed this strategy "network programming. The most important contributions of our paper are the conceptual one and the major advances in modular and scalable molecular computing DNA computing in this case. An open source simulation of C. So far the physics engine Gepetto has been built and models of the neural connectome and a muscle cell have been created in the NeuroML format. Protein structure prediction is the prediction of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of a protein's tertiary structure from its primary structure.
It is one of the most important goals pursued by bioinformatics and theoretical chemistry. Protein structure prediction is of high importance in medicine for example, in drug design and biotechnology for example, in the design of novel enzymes. Every two years, the performance of current methods is assessed in the CASP experiment. The Blue Brain Project is an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the molecular level.
The project is headed by the Institute's director, Henry Markram. Using a Blue Gene supercomputer running Michael Hines's NEURON software , the simulation does not consist simply of an artificial neural network , but involves a partially biologically realistic model of neurons. The last decade has seen the emergence of a growing number of simulations of the immune system. The Virtual Liver project is a 43 million euro research program funded by the German Government, made up of seventy research group distributed across Germany.
The goal is to produce a virtual liver, a dynamic mathematical model that represents human liver physiology , morphology and function.
Computing with cells : advances in membrane computing (Book, ) [abepivurev.tk]
Electronic trees e-trees usually use L-systems to simulate growth. L-systems are very important in the field of complexity science and A-life. A universally accepted system for describing changes in plant morphology at the cellular or modular level has yet to be devised. Ecosystem models are mathematical representations of ecosystems.
Effect of plastic particles on cell membranes
The purpose of models in ecotoxicology is the understanding, simulation and prediction of effects caused by toxicants in the environment. Most current models describe effects on one of many different levels of biological organization e. A challenge is the development of models that predict effects across biological scales. Ecotoxicology and models discusses some types of ecotoxicological models and provides links to many others. It is possible to model the progress of most infectious diseases mathematically to discover the likely outcome of an epidemic or to help manage them by vaccination.
This field tries to find parameters for various infectious diseases and to use those parameters to make useful calculations about the effects of a mass vaccination programme. From Wikipedia, the free encyclopedia. Main article: Cellular model. Main article: Protein folding problem. Main article: Simulated growth of plants. Main article: Ecosystem model.
Main articles: Mathematical modelling of infectious disease and Epidemic model. Essays in Biochemistry. Simulated brain closer to thought , BBC News. Retrieved Archived from the original on Barab, A. Nature Reviews Genetics. Covert; Schilling, C. Journal of Theoretical Biology. Covert, M.
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The Journal of Biological Chemistry. Edwards; Palsson, B. Bibcode : PNAS Bonneau, R. Nature Chemical Biology.