1031:. These artificial creatures were selected for their abilities endowed to swim, or walk, or jump, and they competed for a common limited resource (controlling a cube). The simulation resulted in the evolution of creatures exhibiting surprising behaviour: some developed hands to grab the cube, others developed legs to move towards the cube. This computational approach was further combined with rapid manufacturing technology to actually build the physical robots that virtually evolved. This marked the emergence of the field of
1149:
1638:) and deleting other fragments from the micronuclear copy. From the computational point of view, the study of this gene assembly process led to many challenging research themes and results, such as the Turing universality of various models of this process. From the biological point of view, a plausible hypothesis about the "bioware" that implements the gene-assembly process was proposed, based on
33:, is a terminology introduced to encompass three classes of methods: 1) those that take inspiration from nature for the development of novel problem-solving techniques; 2) those that are based on the use of computers to synthesize natural phenomena; and 3) those that employ natural materials (e.g., molecules) to compute. The main fields of research that compose these three branches are
135:. Efforts to understand biological systems also include engineering of semi-synthetic organisms, and understanding the universe itself from the point of view of information processing. Indeed, the idea was even advanced that information is more fundamental than matter or energy. The Zuse-Fredkin thesis, dating back to the 1960s, states that the entire universe is a huge
617:(EDA), on the other hand, are evolutionary algorithms that substitute traditional reproduction operators by model-guided ones. Such models are learned from the population by employing machine learning techniques and represented as Probabilistic Graphical Models, from which new solutions can be sampled or generated from guided-crossover.
1271:, such as the fact that quantum information cannot be measured reliably and any attempt at measuring it results in an unavoidable and irreversible disturbance. A successful open air experiment in quantum cryptography was reported in 2007, where data was transmitted securely over a distance of 144 km.
1626:. Conjugation of two ciliates consists of the exchange of their micronuclear genetic information, leading to the formation of two new micronuclei, followed by each ciliate re-assembling the information from its new micronucleus to construct a new functional macronucleus. The latter process is called
928:
aims at engineering well-defined shapes and patterns, or coherent computational behaviours, from the local interactions of a multitude of simple unreliable, irregularly placed, asynchronous, identically programmed computing elements (particles). As a programming paradigm, the aim is to find new
1590:
A third approach to engineering semi-synthetic cells is the construction of a single type of RNA-like molecule with the ability of self-replication. Such a molecule could be obtained by guiding the rapid evolution of an initial population of RNA-like molecules, by selection for the desired traits.
1296:
The dual aspect of natural computation is that it aims to understand nature by regarding natural phenomena as information processing. Already in the 1960s, Zuse and
Fredkin suggested the idea that the entire universe is a computational (information processing) mechanism, modelled as a cellular
845:
structure. Each membrane-enveloped region contains objects, transformation rules which modify these objects, as well as transfer rules, which specify whether the objects will be transferred outside or stay inside the region. Regions communicate with each other via the transfer of objects. The
602:
applied the idea of evolutionary computation to the problem of finding a (nearly-)optimal solution to a given problem. Genetic algorithms initially consisted of an input population of individuals encoded as fixed-length bit strings, the genetic operators mutation (bit flips) and recombination
953:
The understanding that the morphology performs computation is used to analyze the relationship between morphology and control and to theoretically guide the design of robots with reduced control requirements, has been used in both robotics and for understanding of cognitive processes in living
1539:
in which proteins and other molecules are embedded, being able to travel along this layer. Through lipid bilayers, substances are transported between the inside and outside of membranes to interact with other molecules. Formalisms depicting transport networks include membrane systems and
1300:
The universe/nature as computational mechanism is elaborated in, exploring the nature with help of the ideas of computability, whilst, based on the idea of nature as network of networks of information processes on different levels of organization, is studying natural processes as computations
152:
The most established "classical" nature-inspired models of computation are cellular automata, neural computation, and evolutionary computation. More recent computational systems abstracted from natural processes include swarm intelligence, artificial immune systems, membrane computing, and
1335:
themselves and the properties of biological systems that arise due to these networks, rather than the individual components of functional processes in an organism. This type of research on organic components has focused strongly on four different interdependent interaction networks:
686:
which depends on its previous velocity (the inertia component), the tendency towards the past personal best position (the nostalgia component), and its tendency towards a global neighborhood optimum or local neighborhood optimum (the social component). Particles thus move through a
1515:
for other chemical reactions, or may chemically modify each other. Such modifications cause changes to available binding sites of proteins. There are tens of thousands of proteins in a cell, and they interact with each other. To describe such a massive scale interactions,
714:
trail on the way back to the nest if they found food, respectively following the concentration of pheromones if they are looking for food. Ant algorithms have been successfully applied to a variety of combinatorial optimization problems over discrete search spaces.
1120:
solely by manipulating DNA strands in test tubes. DNA computations start from an initial input encoded as a DNA sequence (essentially a sequence over the four-letter alphabet {A, C, G, T}), and proceed by a succession of bio-operations such as cut-and-paste (by
1297:
automaton which continuously updates its rules. A recent quantum-mechanical approach of Lloyd suggests the universe as a quantum computer that computes its own behaviour, while Vedral suggests that information is the most fundamental building block of reality.
1330:
Computational systems biology (or simply systems biology) is an integrative and qualitative approach that investigates the complex communications and interactions taking place in biological systems. Thus, in systems biology, the focus of the study is the
973:
Cognitive capacities of present-day cognitive computing are far from human level. The same info-computational approach can be applied to other, simpler living organisms. Bacteria are an example of a cognitive system modelled computationally, see
1558:
Synthetic biology aims at engineering synthetic biological components, with the ultimate goal of assembling whole biological systems from their constituent components. The history of synthetic biology can be traced back to the 1960s, when
1506:
refer to the interactions between proteins, and they perform various mechanical and metabolic tasks inside a cell. Two or more proteins may bind to each other via binding of their interactions sites, and form a dynamic protein complex
143:
that computes its own behaviour. The universe/nature as computational mechanism is addressed by, exploring nature with help the ideas of computability, and studying natural processes as computations (information processing).
1008:(L-systems), that have been used to model plant growth and development. An L-system is a parallel rewriting system that starts with an initial word, and applies its rewriting rules in parallel to all letters of the word.
1275:
is another promising application, in which a quantum state (not matter or energy) is transferred to an arbitrary distant location. Implementations of practical quantum computers are based on various substrates such as
575:). The next generation is obtained from selected individuals (parents) by using genetically inspired operators. The choice of parents can be guided by a selection operator which reflects the biological principle of
2783:
Many of the constituent research areas of natural computing have their own specialized journals and books series. Journals and book series dedicated to the broad field of
Natural Computing include the journals
506:
1520:
were introduced as a graphical notation to depict molecular interactions in succinct pictures. Other approaches to describing accurately and succinctly protein–protein interactions include the use of
1215:
introduced by Tom Head already in 1987) and their computational power has been investigated. Various subsets of bio-operations are now known to be able to achieve the computational power of
1398:. They perform information processing tasks within the cell, including the assembly and maintenance of other networks. Models of gene regulatory networks include random and probabilistic
191:. Cellular automata have been applied to modelling a variety of phenomena such as communication, growth, reproduction, competition, evolution and other physical and biological processes.
401:
337:
603:(combination of a prefix of a parent with the suffix of the other), and a problem-dependent fitness function. Genetic algorithms have been used to optimize computer programs, called
2013:
Martins, Jean P.; Fonseca, Carlos M.; Delbem, Alexandre C. B. (25 December 2014). "On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem".
1614:) is another approach to understand nature as computation. One particular study in this area is that of the computational nature of gene assembly in unicellular organisms called
1288:, etc. As of 2006, the largest quantum computing experiment used liquid state nuclear magnetic resonance quantum information processors, and could operate on up to 12 qubits.
998:(ALife) is a research field whose ultimate goal is to understand the essential properties of life organisms by building, within electronic computers or other artificial media,
520:
by which the weights of the connections in the network are repeatedly adjusted so as to minimize the difference between the vector of actual outputs and that of desired outputs.
1639:
902:
553:
An artificial evolutionary system is a computational system based on the notion of simulated evolution. It comprises a constant- or variable-size population of individuals, a
1532:
1257:
for quantum database search that has a quadratic time advantage, quantum computers were shown to potentially possess a significant benefit relative to electronic computers.
1535:
refer to the separation and transport of substances mediated by lipid membranes. Some lipids can self-assemble into biological membranes. A lipid membrane consists of a
2337:
1574:
Along with the possibility of synthesizing longer and longer DNA strands, the prospect of creating synthetic genomes with the purpose of building entirely artificial
1011:
Pioneering experiments in artificial life included the design of evolving "virtual block creatures" acting in simulated environments with realistic features such as
2651:. In Artificial Life XII Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems, pages 186-193. MIT Press, August 2010.
1197:
271:
1391:
1796:
1403:
775:
966:
Cognitive computing CC is a new type of computing, typically with the goal of modelling of functions of human sensing, reasoning, and response to stimulus, see
1522:
1503:
710:
model the foraging behaviour of ant colonies. To find the best path between the nest and a source of food, ants rely on indirect communication by laying a
608:
2110:
1575:
1578:
became a reality. Indeed, rapid assembly of chemically synthesized short DNA strands made it possible to generate a 5386bp synthetic genome of a virus.
1212:
2805:
Ridge, E.; Kudenko, D.; Kazakov, D.; Curry, E. (2005). "Moving Nature-Inspired
Algorithms to Parallel, Asynchronous and Decentralised Environments".
2644:
1661:
cellular logic gates and genetic circuits that harness the cell's existing biochemical processes (see for example ) and the global optimization of
1627:
1541:
696:
128:
1386:. Genes interact with each other either through their gene products (mRNA, proteins) which can regulate gene transcription, or through small
231:), and to design efficient algorithms based on the principles of how the human brain processes information (Artificial Neural Networks, ANN ).
1201:
516:
selected output neurons. Note that different choices of weights produce different network functions for the same inputs. Back-propagation is a
224:
2097:
1387:
1205:
2182:
1245:
to perform computations. A qubit can hold a "0", a "1", or a quantum superposition of these. A quantum computer operates on qubits with
1587:. This discovery paves the way to the assembly of a minimal but still viable artificial genome consisting of the essential genes only.
1571:
technology, are a precursor of today's synthetic biology which extends these techniques to entire systems of genes and gene products.
1517:
917:(the development of well-defined shapes and functional structures) is achieved by the interactions between cells guided by the genetic
181:. The next state of a cell is computed by a transition rule and it depends only on its current state and the states of its neighbors.
1066:
All of the computational techniques mentioned above, while inspired by nature, have been implemented until now mostly on traditional
2469:
406:
508:. Some neurons are selected to be the output neurons, and the network function is the vectorial function that associates to the
96:, these computational paradigms can be implemented on alternative physical media such as biomolecules (DNA, RNA), or trapped-ion
1133:
that employs the polymerase enzyme), and read-out. Recent experimental research succeeded in solving more complex instances of
1042:
explores a biological implementation of similar ideas. Other research directions within the field of artificial life include
933:
that would work well for amorphous computing environments. Amorphous computing also plays an important role as the basis for "
674:
applies this idea to the problem of finding an optimal solution to a given problem by a search through a (multi-dimensional)
2789:
2856:
2625:
1989:
1956:
1046:
as well as traditionally biological phenomena explored in artificial systems, ranging from computational processes such as
691:
and their personal best. Particle swarm optimization algorithms have been applied to various optimization problems, and to
614:
563:
from the current one. The initial population is typically generated randomly or heuristically, and typical operators are
1417:. This interpretation allows one to compare human-made electronic computation with computation as it occurs in nature.
1168:
process by which objects autonomously come together to form complex structures. Instances in nature abound, and include
583:
eventually converges towards a nearly optimal population of individuals, from the point of view of the fitness function.
2083:
Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Knight Jr., T., Nagpal, R., Rauch, E., Sussman, G., Weiss, R.
2366:
1911:
1755:
Fredkin, F. Digital mechanics: An informational process based on reversible universal CA. Physica D 45 (1990) 254-270
1394:, together with genes' interactions with other substances in the cell, form the most basic interaction network: the
1129:), extraction of strands containing a certain subsequence (by using Watson-Crick complementarity), copy (by using
790:
are abstractions of the natural immune system, emphasizing these computational aspects. Their applications include
1837:
de Castro, L. N., Fundamentals of
Natural Computing: Basic Concepts, Algorithms, and Applications, CRC Press, 2006.
1264:
1112:
The first experimental realization of special-purpose molecular computer was the 1994 breakthrough experiment by
116:
175:. The cellular automaton updates the states of its cells synchronously according to the transition rules given
171:
consisting of an array of cells. Space and time are discrete and each of the cells can be in a finite number of
2518:
2453:
Generating a synthetic genome by whole genome assembly: {phi}X174 bacteriophage from synthetic oligonucleotides
1877:
Bäck, T., Fogel, D., Michalewicz, Z., editors. Handbook of
Evolutionary Computation. IOP Publishing, U.K., 1997
930:
347:
283:
607:, and today they are also applied to real-valued parameter optimization problems as well as to many types of
2246:
1887:
2851:
2259:
2835:
2562:
2641:
1693:
1342:
comprise gene-gene interactions, as well as interactions between genes and other substances in the cell.
1004:
systems that exhibit properties normally associated only with living organisms. Early examples include
747:
671:
64:
Computational paradigms studied by natural computing are abstracted from natural phenomena as diverse as
17:
2563:"Template-guided recombination for IES elimination and unscrambling of genes in stichotrichous ciliates"
2797:
2383:
2276:
1678:
1285:
855:
847:
665:
591:
228:
34:
2712:
This article was written based on the following references with the kind permission of their authors:
2058:
1949:
Hierarchical
Bayesian optimization algorithm : toward a new generation of evolutionary algorithms
1581:
Alternatively, Smith et al. found about 100 genes that can be removed individually from the genome of
1492:
In addition, unlike a conventional computer, robustness in a genomic computer is achieved by various
103:
Dually, one can view processes occurring in nature as information processing. Such processes include
2293:
2216:
2162:
1130:
787:
598:
originally aimed at creating optimal "intelligent agents" modelled, e.g., as finite state machines.
235:
200:
46:
2735:
2422:
1933:
1496:
by which poorly functional processes are rapidly degraded, poorly functional cells are killed by
1211:
Theoretical research in molecular computing has yielded several novel models of DNA computing (e.g.
1141:, and wet DNA implementations of finite state machines with potential applications to the design of
2819:
1711:
1339:
1117:
595:
541:
184:
172:
837:. A generic membrane system (P-system) consists of cell-like compartments (regions) delimited by
139:
which continuously updates its rules. Recently it has been suggested that the whole universe is a
1567:
discovered the mathematical logic in gene regulation. Genetic engineering techniques, based on
1395:
894:
890:
859:
707:
629:
572:
38:
2217:
Toward reliable algorithmic self-assembly of DNA tiles: A fixed-width cellular automaton pattern
2179:
1184:. Examples of self-assembly research topics include self-assembled DNA nanostructures such as
869:
Applications of membrane systems include machine learning, modelling of biological processes (
2814:
2730:
1683:
1594:
Another effort in this field is towards engineering multi-cellular systems by designing, e.g.,
1336:
gene-regulatory networks, biochemical networks, transport networks, and carbohydrate networks.
1142:
1055:
862:, which rules are applied to which objects. The output of the computation is collected from an
700:
2785:
2324:
1635:
1583:
1413:
Another viewpoint is that the entire genomic regulatory system is a computational system, a
1272:
1254:
1238:
955:
739:
692:
568:
108:
2499:
727:) are computational systems inspired by the natural immune systems of biological organisms.
2763:
2663:"Plant behaviour in response to the environment: information processing in the solid state"
2527:
2305:
Paun, G., Rozenberg, G., Salomaa, A. DNA Computing: New
Computing Paradigms. Springer, 1998
1375:
1260:
1242:
1160:
One of the most notable contributions of research in this field is to the understanding of
1043:
1016:
735:
587:
249:
176:
132:
8:
2409:
1730:
G.Rozenberg, T.Back, J.Kok, Editors, Handbook of
Natural Computing, Springer Verlag, 2012
1363:
1332:
1268:
1250:
1185:
1122:
1067:
1005:
967:
925:
846:
computation by a membrane system starts with an initial configuration, where the number (
803:
604:
547:
517:
188:
93:
73:
2767:
2754:
Leandro Nunes de Castro (March 2007). "Fundamentals of
Natural Computing: An Overview".
2531:
2516:
Angeleska, A.; Jonoska, N.; Saito, M.; Landweber, L. (2007). "RNA-guided DNA assembly".
2396:
571:. At each step, the individuals are evaluated according to the given fitness function (
2687:
2662:
2039:
Engelbrecht, A. Fundamentals of
Computational Swarm Intelligence. Wiley and Sons, 2005.
1995:
1921:
1666:
1607:
1493:
1383:
1359:
1106:
1086:
1012:
942:
898:
882:
874:
826:
791:
633:
625:
599:
586:
The study of evolutionary systems has historically evolved along three main branches:
239:
162:
136:
42:
2578:
2439:
2692:
2621:
2582:
2543:
2048:
Dasgupta, D. editor. Artificial Immune Systems and Their Applications. Springer, 1998
1985:
1952:
1907:
1859:
Arbib, M., editor. The Handbook of Brain Theory and Neural Networks. MIT Press, 2003.
1780:
1706:
1701:
1611:
1553:
1228:
938:
886:
795:
743:
688:
682:, each representing a possible solution to the problem. Each particle has its own
554:
205:
Neural computation is the field of research that emerged from the comparison between
124:
58:
2397:
Molecular interaction map of the mammalian cell cycle control and DNA repair systems
2234:
Autonomous programmable biomolecular devices using self-assembled DNA nanostructures
1999:
1560:
1101:, and molecular biology tools act on the data to perform various operations (e.g.,
2771:
2740:
2682:
2674:
2613:
2574:
2535:
2145:
2022:
1977:
1653:
1051:
842:
830:
632:, is defined as the problem solving behavior that emerges from the interaction of
529:
521:
220:
168:
140:
120:
65:
1888:
Genetic Programming: On the Programming of Computers by Means of Natural Selection
2648:
2500:
The evolution of cellular computing: Nature's solution to a computational problem
2370:
2186:
2132:
2071:
2026:
1981:
1847:
1825:
1812:
1740:
1568:
1399:
1325:
1281:
1216:
1113:
995:
975:
799:
783:
724:
525:
341:
112:
50:
2834:
For readers interested in popular science article, consider this one on Medium:
2775:
2452:
2233:
2539:
2470:
A small aptamer with strong and specific recognition of the triphosphate of ATP
2084:
1595:
1367:
1193:
1181:
878:
870:
815:
807:
675:
576:
210:
85:
77:
1165:
2845:
1688:
1564:
1536:
1407:
1347:
1161:
1090:
914:
834:
731:
104:
89:
81:
54:
2745:
2718:
2486:
2363:
1901:
687:
multidimensional space and eventually converge towards a point between the
2696:
2678:
2586:
2547:
1623:
1619:
1508:
1371:
1355:
1246:
1098:
1094:
1972:
Thierens, Dirk (11 September 2010). "The Linkage Tree Genetic Algorithm".
1781:
Programming the Universe: A Quantum Computer Scientist Takes on the Cosmos
1767:
Zuse, K. Rechnender Raum. Elektronische Datenverarbeitung 8 (1967) 336-344
1618:. Ciliates store a copy of their DNA containing functional genes in the
1148:
2203:
1631:
1630:, or gene re-arrangement. It involves re-ordering some fragments of DNA (
1526:
1189:
1134:
1047:
779:
277:
2617:
2601:
1900:
Pelikan, Martin; Goldberg, David E.; CantĂş-Paz, Erick (1 January 1999).
1797:
A Computable Universe: Understanding and Exploring Nature as Computation
1500:, and poorly functional organisms are out-competed by more fit species.
2793:
2612:. Lecture Notes in Computer Science. Vol. 3892. pp. 203–212.
1102:
763:
559:
979:
1512:
1497:
1379:
1173:
1089:(a.k.a. biomolecular computing, biocomputing, biochemical computing,
1024:
1000:
751:
711:
594:
for real-valued as well as discrete and mixed types of parameters.
580:
2600:
Nakagawa, Hirotaka; Sakamoto, Kensaku; Sakakibara, Yasubumi (2006).
2059:
Artificial Immune Systems: A New Computational Intelligence Approach
1868:
Rojas, R. Neural Networks: A Systematic Introduction. Springer, 1996
187:
is one of the best-known examples of cellular automata, shown to be
2790:
Theoretical Computer Science, Series C: Theory of Natural Computing
1277:
1177:
1028:
851:
811:
767:
683:
645:
637:
564:
206:
153:
amorphous computing. Detailed reviews can be found in many books .
2561:
Prescott, David M.; Ehrenfeucht, A.; Rozenberg, G. (7 June 2003).
2215:
Fujibayashi, K., Hariadi, R., Park, S-H., Winfree, E., Murata, S.
2122:
Langton, C., editor. Artificial Life. Addison-Wesley Longman, 1990
1152:
DNA tile self-assembly of a Sierpinski triangle, starting from a
1050:
adaptation and development, to physical processes such as growth,
1662:
1647:
1615:
1351:
1126:
1020:
755:
653:
546:
Evolutionary computation is a computational paradigm inspired by
2111:
How the body shapes the way we think: a new view of intelligence
1665:
aperture in leaves, following a set of local rules resembling a
723:
Artificial immune systems (a.k.a. immunological computation or
1234:
771:
501:{\displaystyle f_{A}(w_{1}x_{1}+w_{2}x_{2}+\ldots +w_{n}x_{n})}
2515:
2716:
1645:
Other approaches to cellular computing include developing an
1169:
759:
661:
215:
69:
2560:
2451:
Smith, H., Hutchison III, C., Pfannkoch, C., and Venter, C.
2180:
Molecular computation of solutions to combinatorial problems
1192:
technique, and DNA nanomachines such as DNA-based circuits (
985:
1343:
1138:
657:
649:
641:
557:, and genetically inspired operators that produce the next
2599:
1233:
A quantum computer processes data stored as quantum bits (
1093:) is a computational paradigm in which data is encoded as
742:
fashion. These include distinguishing between self and
2338:
Benchmarking quantum control methods on a 12-qubit system
664:) which communicate with other agents by acting on their
2804:
2800:(G.Rozenberg, T.Back, J.Kok, Editors, Springer Verlag).
2314:
Hirvensalo, M. Quantum Computing, 2nd Ed. Springer, 2004
1899:
1651:
programmable and autonomous finite-state automaton with
147:
2753:
2399:. Molecular Biology of the Cell 10(8) (1999) 2703-2734.
1200:), ribozymes for logic operations, molecular switches (
850:) of each object is set to some value for each region (
1598:
used to coordinate living bacterial cell populations.
1421:
A comparison between genomic and electronic computers
2830:
by Michael G. Hinchey, Roy Sterritt, and Chris Rouff,
2260:
Algorithmic self-assembly of DNA Sierpinski triangles
2236:. Communications of the ACM 50, 9 (Sept. 2007), 46-53
2204:
DNA computing - the arrival of biological mathematics
2163:
Automatic design and manufacture of robotic lifeforms
885:), as well as computer science applications such as
409:
350:
286:
252:
2012:
1358:. Each gene is associated with other DNA segments (
2660:
2642:
Design principles of transcriptional logic circuits
2440:
Brane calculi: Interactions of biological membranes
2410:
Bio-calculus: its concept and molecular interaction
2277:
Folding DNA to create nanoscale shapes and patterns
2087:. Communications of the ACM 43, 5 (May 2000), 74-82
1826:
Handbook of Bioinspired Algorithms and Applications
1291:
2325:Entanglemen-based quantum communication over 144km
2249:. Scientific American Reports, 17. 3 (2007), 30-39
2206:. The Mathematical Intelligencer 19, 2 (1997) 9-22
1807:
1805:
1237:), and uses quantum mechanical phenomena such as
1070:. In contrast, the two paradigms introduced here,
829:investigates computing models abstracted from the
500:
395:
331:
265:
2667:Philosophical Transactions of the Royal Society B
1304:The main directions of research in this area are
1061:
2843:
2487:Engineered communications for microbial robotics
2408:Nagasaki, M., Onami, S., Miyano, S., Kitano, H.
1078:, employ radically different types of hardware.
730:Viewed as an information processing system, the
2807:Self-Organization and Autonomic Informatics (I)
1802:
2717:Lila Kari, Grzegorz Rozenberg (October 2008).
2442:. In LNCS 3082, pages 257-280. Springer, 2005.
528:can be used to find optimal weights for given
213:. This field aims both to understand how the
2330:
2296:. Nature Nanotechnology 2 (May 2007), 275-284
2146:Artificial life: from robot dreams to reality
1974:Parallel Problem Solving from Nature, PPSN XI
2308:
1188:or arbitrary nanoshapes obtained using the
1137:problems such as a 20-variable instance of
734:of organisms performs many complex tasks in
718:
2423:Cellular abstractions: Cells as computation
2386:. Developmental Biology 310 (2007), 187-195
2269:
2033:
1799:. World Scientific Publishing Company, 2012
1751:
1749:
535:
2489:. In LNCS 2054, pages 1-16, Springer, 2001
2353:Vedral, V. . Oxford University Press, 2010
2258:Rothemund, P., Papadakis, N., Winfree, E.
2042:
1724:
1469:Distinction between hardware and software
948:
2818:
2744:
2734:
2686:
2382:Istrail, S., De-Leon, B-T., Davidson, E.
2172:
2116:
2103:
2090:
1840:
1791:
1789:
1775:
1773:
986:Synthesizing nature by means of computing
396:{\displaystyle w_{1},w_{2},\ldots ,w_{n}}
332:{\displaystyle x_{1},x_{2},\ldots ,x_{n}}
84:, the defining properties of life forms,
2661:Duran-Nebreda S, Bassel G (April 2019).
2474:Journal of the American Chemical Society
2432:
2402:
2373:Bulletin of the EATCS 93 (2007), 176-204
2347:
2239:
2138:
2051:
1971:
1903:BOA: The Bayesian Optimization Algorithm
1831:
1763:
1761:
1746:
1390:that can directly regulate genes. These
1147:
1071:
2445:
2412:. Genome Informatics 10 (1999) 133-143.
2317:
1946:
1862:
1853:
1733:
1313:
934:
2844:
2719:"The Many Facets of Natural Computing"
2634:
2479:
2468:Sazani, P., Larralde, R., Szostak, J.
2415:
2384:The regulatory genome and the computer
2286:
2226:
2209:
2196:
2155:
2125:
2064:
1880:
1818:
1811:Dodig-Crnkovic, G. and Giovagnoli, R.
1786:
1770:
1622:, and another "encrypted" copy in the
1511:). These protein complexes may act as
1309:
1156:obtained by the DNA origami technique
1081:
1075:
1039:
961:
908:
97:
2593:
2462:
2376:
2356:
2299:
2252:
2077:
1871:
1758:
1739:A.Brabazon, M.O'Neill, S.McGarraghy.
1601:
1116:who solved a 7-node instance of the
821:
620:
194:
148:Nature-inspired models of computation
2389:
2364:Abstract machines of systems biology
2133:The Mathematical Theory of L Systems
1606:Computation in living cells (a.k.a.
1547:
1305:
1267:, but on the special properties of
1222:
1204:), and autonomous molecular motors (
678:. The initial set-up is a swarm of
615:Estimation of Distribution Algorithm
156:
2606:Computer Based on Escherichia coli"
2247:Nanotechnology and the double helix
2072:Membrane Computing: An Introduction
1951:(1st ed.). Berlin : Springer.
1529:enriched with stochastic features.
1172:binding by chemical bonds to form
13:
2707:
1596:cell-to-cell communication modules
1319:
990:
14:
2868:
2794:the Natural Computing book series
2327:. Nature Physics 3 (2007) 481-486
1350:(mRNA), and then translated into
901:, as well as analysis of various
512:input values, the outputs of the
1292:Nature as information processing
119:networks, biological transport (
16:For the scientific journal, see
2654:
2554:
2509:
2492:
2006:
1965:
1940:
1893:
1828:, Chapman & Hall/CRC, 2005.
921:encoded in the organism's DNA.
592:parameter optimization problems
526:backwards propagation of errors
2567:Journal of Theoretical Biology
2519:Journal of Theoretical Biology
2131:Rozenberg, G. and Salomaa, A.
2109:Pfeifer, R. and Bondgard, J.
1906:. Gecco'99. pp. 525–532.
1062:Nature-inspired novel hardware
579:. This process of simulated
495:
420:
1:
2828:Swarms and Swarm Intelligence
2798:Handbook of Natural Computing
2579:10.1016/S0022-5193(03)00037-7
2096:Pfeifer, R. and FĂĽchslin R.
1850:. Yale University Press, 1958
1717:
1657:, designing and constructing
1640:template guided recombination
1265:complexity of the computation
903:computationally hard problems
854:). It proceeds by choosing,
246:is equipped with a function
2857:Theoretical computer science
2640:Zabet NR, Hone ANW, Chu DF
2027:10.1016/j.neucom.2014.04.069
1982:10.1007/978-3-642-15844-5_27
1741:Natural Computing Algorithms
1253:for factoring integers, and
833:of living cells affected by
7:
2796:(Springer Verlag), and the
2776:10.1016/j.plrev.2006.10.002
2498:Landweber, L. and Kari, L.
2485:Weiss, R., Knight, Jr., T.
1672:
1251:Shor's polynomial algorithm
881:in bacteria, cell-mediated
831:compartmentalized structure
672:Particle swarm optimization
628:, sometimes referred to as
117:protein–protein interaction
10:
2873:
2836:Nature-Inspired Algorithms
2540:10.1016/j.jtbi.2007.06.007
2476:, 126(27) (2004) 8370-8371
2292:Bath, J., Turberfield, A.
2057:de Castro, L., Timmis, J.
1848:The Computer and the Brain
1824:Olarius S., Zomaya A. Y.,
1679:Computational intelligence
1551:
1323:
1301:(information processing).
1286:nuclear magnetic resonance
1226:
1033:mechanical artificial life
866:determined output region.
798:in a time series of data,
539:
518:supervised learning method
229:computational neuroscience
198:
167:A cellular automaton is a
160:
35:artificial neural networks
15:
2723:Communications of the ACM
2459:, 26 (2003), 15440-15445.
1131:polymerase chain reaction
956:Morphological computation
913:In biological organisms,
860:maximally parallel manner
788:Artificial immune systems
719:Artificial immune systems
236:artificial neural network
201:Artificial neural network
189:computationally universal
68:, the functioning of the
47:artificial immune systems
2232:Reif, J. and LaBean, T.
2161:Lipson, P., Pollack, J.
2100:. (starts at p.11), 2013
1947:Pelikan, Martin (2005).
1712:Unconventional computing
1447:Components construction
1396:gene regulatory networks
1340:Gene regulatory networks
1176:, and molecules forming
1164:. Self-assembly is the
1118:Hamiltonian Path Problem
792:computer virus detection
596:Evolutionary programming
542:Evolutionary computation
536:Evolutionary computation
532:and input-output pairs.
242:. An artificial neuron
2756:Physics of Life Reviews
2746:10.1145/1400181.1400200
2421:Regev, A., Shapiro, E.
2342:Physical Review Letters
2336:Negrevergne, C. et al.
2185:6 February 2005 at the
2098:Morphological Computing
1743:, Springer Verlag, 2015
1198:bit-wise cumulative XOR
949:Morphological computing
924:Inspired by this idea,
891:public-key cryptography
841:, that are placed in a
630:collective intelligence
573:survival of the fittest
530:topology of the network
109:developmental processes
92:. Besides traditional
39:evolutionary algorithms
2679:10.1098/rstb.2018.0370
2506:, 52, 1/3 (1999) 3-13.
2266:2, 12 (December 2004)
2223:8(7) (2007) 1791-1797.
2135:. Academic Press, 1980
1684:Bio-inspired computing
1392:gene-gene interactions
1157:
931:programming techniques
590:provide a solution to
502:
397:
333:
267:
2369:19 April 2008 at the
2193:266 (1994), 1021-1024
1584:Mycoplasma Genitalium
1404:asynchronous automata
1346:are transcribed into
1273:Quantum teleportation
1151:
776:associative retrieval
740:distributed computing
732:natural immune system
693:unsupervised learning
503:
398:
334:
268:
266:{\displaystyle f_{A}}
199:Further information:
185:Conway's Game of Life
133:unicellular organisms
2647:7 March 2012 at the
1976:. pp. 264–273.
1523:textual bio-calculus
1504:Biochemical networks
1431:Electronic computer
1333:interaction networks
1263:is not based on the
1261:Quantum cryptography
1186:Sierpinski triangles
1044:artificial chemistry
856:nondeterministically
806:, machine learning,
588:Evolution strategies
407:
348:
284:
250:
49:, fractal geometry,
2852:Natural computation
2788:(Springer Verlag),
2768:2007PhLRv...4....1D
2618:10.1007/11753681_16
2602:"Development of an
2532:2007JThBi.248..706A
2283:440 (2006) 297-302.
2169:406 (2000), 974-978
2152:406 (2000), 945-947
2085:Amorphous computing
1576:synthetic organisms
1494:feedback mechanisms
1464:temporal synchrony
1461:causal coordination
1422:
1269:quantum information
1247:quantum logic gates
1123:restriction enzymes
1087:Molecular computing
1082:Molecular computing
1072:molecular computing
1068:electronic hardware
1006:Lindenmayer systems
968:Cognitive computing
962:Cognitive computing
926:amorphous computing
909:Amorphous computing
852:multiset of objects
843:nested hierarchical
804:pattern recognition
706:In the same vein,
609:combinatorial tasks
605:genetic programming
548:Darwinian evolution
522:Learning algorithms
94:electronic hardware
74:Darwinian evolution
31:natural computation
2673:(1774): 20180370.
2344:96:art170501, 2006
1667:cellular automaton
1608:cellular computing
1602:Cellular computing
1533:Transport networks
1483:molecules and ions
1420:
1384:gene transcription
1314:cellular computing
1255:Grover's algorithm
1158:
1107:logical operations
943:cellular computing
937:" (see the topics
935:cellular computing
899:sorting algorithms
875:signaling pathways
827:Membrane computing
822:Membrane computing
666:local environments
626:Swarm intelligence
621:Swarm intelligence
600:Genetic algorithms
498:
403:, and it outputs
393:
329:
263:
240:artificial neurons
207:computing machines
195:Neural computation
163:Cellular automaton
137:cellular automaton
43:swarm intelligence
2786:Natural Computing
2627:978-3-540-34161-1
2323:Ursin, R. et al.
2113:. MIT Press, 2006
2061:. Springer, 2002.
1991:978-3-642-15843-8
1958:978-3-540-23774-7
1890:. MIT Press, 1992
1707:Synthetic biology
1702:Quantum computing
1695:Natural Computing
1612:in-vivo computing
1554:Synthetic biology
1548:Synthetic biology
1490:
1489:
1354:according to the
1310:synthetic biology
1229:Quantum computing
1223:Quantum computing
1076:quantum computing
1040:synthetic biology
939:synthetic biology
887:computer graphics
796:anomaly detection
634:individual agents
555:fitness criterion
157:Cellular automata
125:passive transport
98:quantum computing
59:quantum computing
27:Natural computing
19:Natural Computing
2864:
2824:
2822:
2779:
2750:
2748:
2738:
2701:
2700:
2690:
2658:
2652:
2638:
2632:
2631:
2597:
2591:
2590:
2558:
2552:
2551:
2513:
2507:
2496:
2490:
2483:
2477:
2466:
2460:
2449:
2443:
2436:
2430:
2419:
2413:
2406:
2400:
2393:
2387:
2380:
2374:
2360:
2354:
2351:
2345:
2334:
2328:
2321:
2315:
2312:
2306:
2303:
2297:
2294:DNA nanomachines
2290:
2284:
2273:
2267:
2256:
2250:
2243:
2237:
2230:
2224:
2213:
2207:
2200:
2194:
2176:
2170:
2159:
2153:
2142:
2136:
2129:
2123:
2120:
2114:
2107:
2101:
2094:
2088:
2081:
2075:
2074:. Springer, 2002
2068:
2062:
2055:
2049:
2046:
2040:
2037:
2031:
2030:
2010:
2004:
2003:
1969:
1963:
1962:
1944:
1938:
1937:
1931:
1927:
1925:
1917:
1897:
1891:
1884:
1878:
1875:
1869:
1866:
1860:
1857:
1851:
1846:von Neumann, J.
1844:
1838:
1835:
1829:
1822:
1816:
1815:. Springer, 2013
1813:COMPUTING NATURE
1809:
1800:
1793:
1784:
1777:
1768:
1765:
1756:
1753:
1744:
1737:
1731:
1728:
1480:Transport media
1428:Genomic computer
1423:
1419:
1415:genomic computer
1400:Boolean networks
1213:splicing systems
1052:self-replication
810:, optimization,
507:
505:
504:
499:
494:
493:
484:
483:
465:
464:
455:
454:
442:
441:
432:
431:
419:
418:
402:
400:
399:
394:
392:
391:
373:
372:
360:
359:
339:with respective
338:
336:
335:
330:
328:
327:
309:
308:
296:
295:
272:
270:
269:
264:
262:
261:
238:is a network of
221:living organisms
169:dynamical system
141:quantum computer
127:) networks, and
121:active transport
66:self-replication
61:, among others.
2872:
2871:
2867:
2866:
2865:
2863:
2862:
2861:
2842:
2841:
2736:10.1.1.141.1586
2710:
2708:Further reading
2705:
2704:
2659:
2655:
2649:Wayback Machine
2639:
2635:
2628:
2598:
2594:
2559:
2555:
2514:
2510:
2497:
2493:
2484:
2480:
2467:
2463:
2450:
2446:
2437:
2433:
2420:
2416:
2407:
2403:
2394:
2390:
2381:
2377:
2371:Wayback Machine
2361:
2357:
2352:
2348:
2335:
2331:
2322:
2318:
2313:
2309:
2304:
2300:
2291:
2287:
2274:
2270:
2257:
2253:
2244:
2240:
2231:
2227:
2214:
2210:
2201:
2197:
2187:Wayback Machine
2177:
2173:
2160:
2156:
2143:
2139:
2130:
2126:
2121:
2117:
2108:
2104:
2095:
2091:
2082:
2078:
2069:
2065:
2056:
2052:
2047:
2043:
2038:
2034:
2011:
2007:
1992:
1970:
1966:
1959:
1945:
1941:
1929:
1928:
1919:
1918:
1914:
1898:
1894:
1885:
1881:
1876:
1872:
1867:
1863:
1858:
1854:
1845:
1841:
1836:
1832:
1823:
1819:
1810:
1803:
1794:
1787:
1778:
1771:
1766:
1759:
1754:
1747:
1738:
1734:
1729:
1725:
1720:
1675:
1604:
1569:recombinant DNA
1556:
1550:
1453:from the start
1450:as-needed basis
1328:
1326:Systems biology
1322:
1320:Systems biology
1306:systems biology
1294:
1282:superconductors
1231:
1225:
1217:Turing machines
1114:Leonard Adleman
1084:
1064:
1048:co-evolutionary
996:Artificial life
993:
991:Artificial life
988:
976:Eshel Ben-Jacob
964:
954:organisms, see
951:
911:
824:
800:fault diagnosis
784:fault-tolerance
780:self-regulation
725:immunocomputing
721:
623:
544:
538:
489:
485:
479:
475:
460:
456:
450:
446:
437:
433:
427:
423:
414:
410:
408:
405:
404:
387:
383:
368:
364:
355:
351:
349:
346:
345:
323:
319:
304:
300:
291:
287:
285:
282:
281:
257:
253:
251:
248:
247:
203:
197:
165:
159:
150:
113:gene regulation
51:artificial life
24:
12:
11:
5:
2870:
2860:
2859:
2854:
2832:
2831:
2825:
2820:10.1.1.64.3403
2781:
2780:
2751:
2709:
2706:
2703:
2702:
2653:
2633:
2626:
2592:
2573:(3): 323–330.
2553:
2526:(4): 706–720.
2508:
2491:
2478:
2461:
2444:
2431:
2429:419 (2002) 343
2414:
2401:
2388:
2375:
2355:
2346:
2329:
2316:
2307:
2298:
2285:
2275:Rothemund, P.
2268:
2251:
2238:
2225:
2208:
2195:
2171:
2154:
2137:
2124:
2115:
2102:
2089:
2076:
2063:
2050:
2041:
2032:
2015:Neurocomputing
2005:
1990:
1964:
1957:
1939:
1930:|journal=
1912:
1892:
1879:
1870:
1861:
1852:
1839:
1830:
1817:
1801:
1785:
1769:
1757:
1745:
1732:
1722:
1721:
1719:
1716:
1715:
1714:
1709:
1704:
1699:
1691:
1686:
1681:
1674:
1671:
1603:
1600:
1561:François Jacob
1552:Main article:
1549:
1546:
1488:
1487:
1484:
1481:
1477:
1476:
1473:
1470:
1466:
1465:
1462:
1459:
1455:
1454:
1451:
1448:
1444:
1443:
1440:
1437:
1433:
1432:
1429:
1426:
1408:network motifs
1370:) that act as
1324:Main article:
1321:
1318:
1293:
1290:
1227:Main article:
1224:
1221:
1194:binary counter
1182:macromolecules
1083:
1080:
1063:
1060:
992:
989:
987:
984:
963:
960:
950:
947:
910:
907:
879:quorum sensing
871:photosynthesis
823:
820:
808:bioinformatics
748:neutralization
720:
717:
708:ant algorithms
703:applications.
676:solution space
622:
619:
577:mate selection
540:Main article:
537:
534:
497:
492:
488:
482:
478:
474:
471:
468:
463:
459:
453:
449:
445:
440:
436:
430:
426:
422:
417:
413:
390:
386:
382:
379:
376:
371:
367:
363:
358:
354:
326:
322:
318:
315:
312:
307:
303:
299:
294:
290:
260:
256:
211:nervous system
209:and the human
196:
193:
161:Main article:
158:
155:
149:
146:
86:cell membranes
78:group behavior
29:, also called
9:
6:
4:
3:
2:
2869:
2858:
2855:
2853:
2850:
2849:
2847:
2840:
2838:
2837:
2829:
2826:
2821:
2816:
2812:
2808:
2803:
2802:
2801:
2799:
2795:
2792:(Elsevier),
2791:
2787:
2777:
2773:
2769:
2765:
2761:
2757:
2752:
2747:
2742:
2737:
2732:
2729:(10): 72–83.
2728:
2724:
2720:
2715:
2714:
2713:
2698:
2694:
2689:
2684:
2680:
2676:
2672:
2668:
2664:
2657:
2650:
2646:
2643:
2637:
2629:
2623:
2619:
2615:
2611:
2610:DNA Computing
2607:
2605:
2596:
2588:
2584:
2580:
2576:
2572:
2568:
2564:
2557:
2549:
2545:
2541:
2537:
2533:
2529:
2525:
2521:
2520:
2512:
2505:
2501:
2495:
2488:
2482:
2475:
2471:
2465:
2458:
2454:
2448:
2441:
2438:Cardelli, L.
2435:
2428:
2424:
2418:
2411:
2405:
2398:
2392:
2385:
2379:
2372:
2368:
2365:
2362:Cardelli, L.
2359:
2350:
2343:
2339:
2333:
2326:
2320:
2311:
2302:
2295:
2289:
2282:
2278:
2272:
2265:
2261:
2255:
2248:
2242:
2235:
2229:
2222:
2218:
2212:
2205:
2199:
2192:
2188:
2184:
2181:
2175:
2168:
2164:
2158:
2151:
2147:
2141:
2134:
2128:
2119:
2112:
2106:
2099:
2093:
2086:
2080:
2073:
2067:
2060:
2054:
2045:
2036:
2028:
2024:
2020:
2016:
2009:
2001:
1997:
1993:
1987:
1983:
1979:
1975:
1968:
1960:
1954:
1950:
1943:
1935:
1923:
1915:
1913:9781558606111
1909:
1905:
1904:
1896:
1889:
1883:
1874:
1865:
1856:
1849:
1843:
1834:
1827:
1821:
1814:
1808:
1806:
1798:
1792:
1790:
1783:. Knopf, 2006
1782:
1776:
1774:
1764:
1762:
1752:
1750:
1742:
1736:
1727:
1723:
1713:
1710:
1708:
1705:
1703:
1700:
1698:
1696:
1692:
1690:
1689:DNA computing
1687:
1685:
1682:
1680:
1677:
1676:
1670:
1668:
1664:
1660:
1656:
1655:
1650:
1649:
1643:
1641:
1637:
1634:and possibly
1633:
1629:
1628:gene assembly
1625:
1621:
1617:
1613:
1609:
1599:
1597:
1592:
1588:
1586:
1585:
1579:
1577:
1572:
1570:
1566:
1565:Jacques Monod
1562:
1555:
1545:
1543:
1542:brane calculi
1538:
1537:lipid bilayer
1534:
1530:
1528:
1524:
1519:
1514:
1510:
1505:
1501:
1499:
1495:
1485:
1482:
1479:
1478:
1474:
1471:
1468:
1467:
1463:
1460:
1458:Coordination
1457:
1456:
1452:
1449:
1446:
1445:
1441:
1438:
1436:Architecture
1435:
1434:
1430:
1427:
1425:
1424:
1418:
1416:
1411:
1409:
1405:
1401:
1397:
1393:
1389:
1385:
1381:
1377:
1373:
1372:binding sites
1369:
1365:
1361:
1357:
1353:
1349:
1348:messenger RNA
1345:
1341:
1337:
1334:
1327:
1317:
1315:
1311:
1307:
1302:
1298:
1289:
1287:
1283:
1279:
1274:
1270:
1266:
1262:
1258:
1256:
1252:
1248:
1244:
1240:
1239:superposition
1236:
1230:
1220:
1218:
1214:
1209:
1207:
1203:
1199:
1195:
1191:
1187:
1183:
1179:
1175:
1171:
1167:
1163:
1162:self-assembly
1155:
1150:
1146:
1144:
1140:
1136:
1132:
1128:
1124:
1119:
1115:
1110:
1108:
1104:
1100:
1096:
1092:
1091:DNA computing
1088:
1079:
1077:
1073:
1069:
1059:
1057:
1053:
1049:
1045:
1041:
1038:The field of
1036:
1034:
1030:
1026:
1022:
1018:
1014:
1009:
1007:
1003:
1002:
997:
983:
981:
980:Microbes-mind
977:
971:
969:
959:
957:
946:
944:
940:
936:
932:
927:
922:
920:
916:
915:morphogenesis
906:
904:
900:
896:
895:approximation
892:
888:
884:
880:
876:
872:
867:
865:
861:
857:
853:
849:
844:
840:
836:
832:
828:
819:
817:
813:
809:
805:
801:
797:
793:
789:
785:
781:
777:
773:
769:
765:
761:
757:
753:
749:
745:
741:
737:
733:
728:
726:
716:
713:
709:
704:
702:
698:
697:game learning
694:
690:
685:
681:
677:
673:
669:
667:
663:
659:
655:
651:
647:
643:
639:
635:
631:
627:
618:
616:
612:
610:
606:
601:
597:
593:
589:
584:
582:
578:
574:
570:
569:recombination
566:
562:
561:
556:
551:
549:
543:
533:
531:
527:
523:
519:
515:
511:
490:
486:
480:
476:
472:
469:
466:
461:
457:
451:
447:
443:
438:
434:
428:
424:
415:
411:
388:
384:
380:
377:
374:
369:
365:
361:
356:
352:
344:
343:
324:
320:
316:
313:
310:
305:
301:
297:
292:
288:
279:
276:
258:
254:
245:
241:
237:
232:
230:
226:
222:
218:
217:
212:
208:
202:
192:
190:
186:
182:
180:
179:
174:
170:
164:
154:
145:
142:
138:
134:
130:
129:gene assembly
126:
122:
118:
114:
110:
106:
105:self-assembly
101:
99:
95:
91:
90:morphogenesis
87:
83:
82:immune system
79:
75:
71:
67:
62:
60:
56:
55:DNA computing
52:
48:
44:
40:
36:
32:
28:
22:
20:
2839:
2833:
2827:
2810:
2806:
2782:
2759:
2755:
2726:
2722:
2711:
2670:
2666:
2656:
2636:
2609:
2603:
2595:
2570:
2566:
2556:
2523:
2517:
2511:
2503:
2494:
2481:
2473:
2464:
2456:
2447:
2434:
2426:
2417:
2404:
2391:
2378:
2358:
2349:
2341:
2332:
2319:
2310:
2301:
2288:
2280:
2271:
2264:PLoS Biology
2263:
2254:
2241:
2228:
2221:Nano Letters
2220:
2211:
2198:
2190:
2178:Adleman, L.
2174:
2166:
2157:
2149:
2140:
2127:
2118:
2105:
2092:
2079:
2066:
2053:
2044:
2035:
2018:
2014:
2008:
1973:
1967:
1948:
1942:
1902:
1895:
1882:
1873:
1864:
1855:
1842:
1833:
1820:
1735:
1726:
1694:
1658:
1652:
1646:
1644:
1632:permutations
1624:micronucleus
1620:macronucleus
1605:
1593:
1589:
1582:
1580:
1573:
1557:
1531:
1509:complexation
1502:
1491:
1414:
1412:
1356:genetic code
1338:
1329:
1303:
1299:
1295:
1259:
1243:entanglement
1232:
1210:
1202:DNA tweezers
1159:
1153:
1111:
1095:biomolecules
1085:
1065:
1037:
1032:
1010:
999:
994:
972:
965:
952:
923:
918:
912:
868:
863:
848:multiplicity
838:
825:
758:, bacteria,
729:
722:
705:
679:
670:
624:
613:
585:
558:
552:
545:
513:
509:
340:
274:
243:
233:
225:brain theory
214:
204:
183:
177:
166:
151:
102:
63:
30:
26:
25:
18:
2762:(1): 1–36.
2245:Seeman, N.
2144:Brooks. R.
1527:pi-calculus
1388:RNA species
1249:. Through
1206:DNA walkers
1190:DNA origami
1143:smart drugs
1135:NP-complete
1099:DNA strands
1056:self-repair
750:of nonself
689:global best
278:real-valued
273:, receives
2846:Categories
2504:Biosystems
1795:Zenil, H.
1779:Lloyd, S.
1718:References
1439:changeable
1380:repressors
1376:activators
1103:arithmetic
945:, below).
873:, certain
701:scheduling
560:generation
115:networks,
2815:CiteSeerX
2813:: 35–49.
2731:CiteSeerX
2395:Kohn, K.
2202:Kari, L.
2070:Paun, G.
2021:: 17–29.
1932:ignored (
1922:cite book
1886:Koza, J.
1636:inversion
1518:Kohn maps
1513:catalysts
1498:apoptosis
1368:silencers
1364:enhancers
1360:promoters
1278:ion-traps
1174:molecules
1166:bottom-up
1025:collision
1001:ab initio
858:and in a
839:membranes
835:membranes
764:parasites
752:pathogens
712:pheromone
680:particles
581:evolution
524:based on
470:…
378:…
314:…
223:works (
100:devices.
21:(journal)
2697:31006360
2645:Archived
2587:12732478
2548:17669433
2457:PNAS 100
2367:Archived
2183:Archived
2000:28648829
1673:See also
1616:ciliates
1352:proteins
1178:crystals
1097:such as
1029:friction
1017:dynamics
1013:kinetics
883:immunity
864:a priori
812:robotics
768:learning
736:parallel
684:velocity
646:termites
638:bacteria
565:mutation
178:a priori
2764:Bibcode
2688:6553596
2604:in vivo
2528:Bibcode
2191:Science
1697:journal
1663:stomata
1659:in vivo
1654:E. coli
1648:in vivo
1127:ligases
1021:gravity
970:and .
958:and .
919:program
816:control
756:viruses
744:nonself
654:spiders
636:(e.g.,
342:weights
280:inputs
2817:
2733:
2695:
2685:
2624:
2585:
2546:
2427:Nature
2281:Nature
2167:Nature
2150:Nature
1998:
1988:
1955:
1910:
1486:wires
1442:rigid
1406:, and
1235:qubits
1054:, and
1027:, and
782:, and
772:memory
762:, and
699:, and
173:states
88:, and
80:, the
57:, and
1996:S2CID
1610:, or
1366:, or
1344:Genes
1170:atoms
760:fungi
662:birds
216:brain
70:brain
2693:PMID
2622:ISBN
2583:PMID
2544:PMID
1986:ISBN
1953:ISBN
1934:help
1908:ISBN
1563:and
1475:Yes
1382:for
1374:for
1312:and
1241:and
1154:seed
1139:3SAT
1125:and
1074:and
978:and
941:and
897:and
814:and
738:and
658:fish
650:bees
642:ants
567:and
2811:135
2772:doi
2741:doi
2683:PMC
2675:doi
2671:374
2614:doi
2575:doi
2571:222
2536:doi
2524:248
2023:doi
2019:146
1978:doi
1525:or
1378:or
1280:,
1208:).
1180:or
1109:).
1105:or
786:.
766:),
234:An
227:or
219:of
131:in
107:,
2848::
2809:.
2770:.
2758:.
2739:.
2727:51
2725:.
2721:.
2691:.
2681:.
2669:.
2665:.
2620:.
2608:.
2581:.
2569:.
2565:.
2542:.
2534:.
2522:.
2502:.
2472:.
2455:.
2425:.
2340:.
2279:.
2262:.
2219:.
2189:.
2165:.
2148:.
2017:.
1994:.
1984:.
1926::
1924:}}
1920:{{
1804:^
1788:^
1772:^
1760:^
1748:^
1669:.
1642:.
1544:.
1472:No
1410:.
1402:,
1362:,
1316:.
1308:,
1284:,
1219:.
1196:,
1145:.
1058:.
1035:.
1023:,
1019:,
1015:,
982:.
905:.
893:,
889:,
877:,
818:.
802:,
794:,
778:,
774:,
770:,
746:,
695:,
668:.
660:,
656:,
652:,
648:,
644:,
640:,
611:.
550:.
123:,
111:,
76:,
72:,
53:,
45:,
41:,
37:,
2823:.
2778:.
2774::
2766::
2760:4
2749:.
2743::
2699:.
2677::
2630:.
2616::
2589:.
2577::
2550:.
2538::
2530::
2029:.
2025::
2002:.
1980::
1961:.
1936:)
1916:.
1507:(
754:(
514:m
510:n
496:)
491:n
487:x
481:n
477:w
473:+
467:+
462:2
458:x
452:2
448:w
444:+
439:1
435:x
429:1
425:w
421:(
416:A
412:f
389:n
385:w
381:,
375:,
370:2
366:w
362:,
357:1
353:w
325:n
321:x
317:,
311:,
306:2
302:x
298:,
293:1
289:x
275:n
259:A
255:f
244:A
23:.
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.