The concept ofbiological computationproposes that livingorganismsperform computations, and that as such, abstract ideas ofinformationandcomputationmay be key to understanding biology.[1][2]As a field, biological computation can include the study of thesystems biologycomputations performed bybiota[3][4][5][6][7]the design ofalgorithmsinspired by the computational methods of biota,[8]thedesignandengineeringof manufactured computational devices usingsynthetic biologycomponents[9][10]and computer methods for the analysis of biological data,[11]elsewhere calledcomputational biologyorbioinformatics.
According to Dominique Chu, Mikhail Prokopenko, and J. Christian J. Ray, "the most important class ofnatural computerscan be found inbiological systemsthat perform computation on multiple levels. From molecular and cellularinformation processingnetworks toecologies,economies and brains, life computes. Despite ubiquitous agreement on this fact going back as far asvon Neumann automataandMcCulloch–Pitts neural nets,we so far lack principles to understand rigorously how computation is done in living, or active, matter ".[12]
Logical circuits can be built withslime moulds.[13]Distributed systemsexperiments have used them to approximate motorway graphs.[14]The slime mouldPhysarum polycephalumis able to compute high-quality approximate solutions to theTraveling Salesman Problem,a combinatorial test with exponentially increasing complexity, inlinear time.[15]Fungi such asbasidiomycetescan also be used to build logical circuits. In a proposed fungal computer, information is represented by spikes of electrical activity, a computation is implemented in amyceliumnetwork, and aninterfaceis realized via fruit bodies.[16]
See also
editReferences
edit- ^Mitchell M (2010-09-21)."Biological Computation".Computer Science Faculty Publications and Presentations.
- ^Didales, K. (2006)Living Computers - Intelligent Plastic Machines.
- ^Didales K (2007)."Being - Our New Understanding of the Meaning of Life".
- ^Bray D (2009).Wetware: a computer in every living cell.New Haven: Yale University Press.ISBN978-0-300-14173-3.
- ^Mitchell M (2010)."Biological Computation"(PDF).Archived fromthe original(PDF)on 2013-10-23.
- ^"Information and entropy in biological systems".NIMBios Workshop.2015.
- ^Dean C (2019)."How Plants Recognise Seasons Using Molecular Memory".The Royal Institution.
- ^Lamm E, Unger R (2011).Biological Computation.Chapman and Hall/CRC.
- ^Biological Computation Group at MIT - Psrg.csail.mit.edu"Biological Computation Group at MIT".Archived fromthe originalon 2013-10-30.Retrieved2013-10-23.
- ^Regot S, Macia J, Conde N, Furukawa K, Kjellén J, Peeters T, et al. (January 2011). "Distributed biological computation with multicellular engineered networks".Nature.469(7329): 207–11.Bibcode:2011Natur.469..207R.doi:10.1038/nature09679.PMID21150900.S2CID4389216.
- ^"Biological Computation".Microsoft Research.
- ^Chu D, Prokopenko M, Ray JC (2018-12-06)."Computation by natural systems".Interface Focus.8(6): 20180058.doi:10.1098/rsfs.2018.0058.PMC6227810.
- ^"Computing with slime: Logical circuits built using living slime molds".ScienceDaily.Retrieved2019-12-06.
- ^Adamatzky A, Akl S, Alonso-Sanz R, Van Dessel W, Ibrahim Z, Ilachinski A, et al. (2013-06-01). "Are motorways rational from slime mould's point of view?".International Journal of Parallel, Emergent and Distributed Systems.28(3): 230–248.arXiv:1203.2851.doi:10.1080/17445760.2012.685884.ISSN1744-5760.S2CID15534238.
- ^"Slime Mold Can Solve Exponentially Complicated Problems in Linear Time | Biology, Computer Science | Sci-News.com".Breaking Science News | Sci-News.com.Retrieved2019-12-06.
- ^Adamatzky A (December 2018)."Towards fungal computer".Interface Focus.8(6): 20180029.doi:10.1098/rsfs.2018.0029.PMC6227805.PMID30443330.
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