Computational Thinking - Учебное пособие, страница 8

Finally, in the caseof a genomic computer, the distinction between hardware andsoftware breaks down: the genomic DNA provides both thehardware and the digital regulatory code (software).41While systems biology studies complex biological organisms asintegrated wholes, synthetic biology is an effort to engineerartificial biological systems from their constituent parts for thepurpose of understanding natural phenomena, or for a varietyof possible applications. The mantra of synthetic biology isthat one can understand only what one can construct.

In thissense, one can make an analogy between synthetic biologyand computer engineering.Advances in DNA synthesis of longer and longer strands ofDNA are paving the way for the construction of syntheticgenomes with the purpose of building an entirely artificialorganism. Progress includes the generation of a 5,386 bpsynthetic genome of a virus, by rapid (14 day) assembly ofchemically synthesized short DNA strands.Besides systems biology that tries to understand biologicalorganisms as networks of interactions, and synthetic biologythat seeks to engineer and build artificial biological systems,another approach to understanding nature as computation isthe research on computation in living cells.

This is alsosometimes called cellular computing, or in vivo computing,and one particular study in this area is that of thecomputational capabilities of gene assembly in unicellularorganisms called ciliates.The process of gene assembly is fascinating from both thebiological and the computational point of view.

From thecomputational point of view, this study led to many novel andchallenging research themes. It was proved that variousmodels of gene assembly have full Turing machinecapabilities. From the biological point of view, the joint effortof computer scientists and biologists led to a plausiblehypothesis (supported already by some experimental data)about the “bioware” that implements the process of geneassembly, which is based on the new concept of templateguided recombination.Other approaches to cellular computing include developing ofan in vivo programmable and autonomous finite-stateautomaton within E.Coli, and designing and constructing in42vivo cellular logic gates and genetic circuits that harness thecell’s existing biochemical processes.Natural sciences: Ours to DiscoverScience advances in ever-widening circles of knowledge.Sometimes it meticulously crawls.

Other times it leaps to anew dimension of understanding and, in the process, itreinvents itself. As the natural sciences are rapidly absorbingideas of information processing, and the meaning ofcomputation is changing as it embraces concepts from thenatural sciences, we have the rare privilege to take part insuch metamorphoses.At this moment natural scientists are awash in wave aftergigantic wave of experimentalbiological data. Justunderneath this tumultuous surface lie ingenious algorithmswaiting to be designed, elegant theorems waiting to be proven,natural laws waiting to be discovered that will put order intochaos.

For, as Spinoza wrote, “nothing happens in nature thatdoes not follow from her laws”.Conversely, there is an abundance of natural phenomenawhich can inspire computing paradigms, alternative physicalsubstrates on which to implement computations, whileviewing various natural processes as computations has becomemore and more essential, desirable, and inevitable. All thesedevelopments are challenging our assumptions aboutcomputation, and indeed, our very definition of it. In thesetimes our task is to discover a new, broader, notion ofcomputation, and to understand the world around us in termsof information processing.Notes:Stanislaw Ulam – a mathematician, together with John vonNeumann discovered a concept of a cellular automaton in the1940sJohn von Nemann – a mathematician, physicist, andpolymath, contributed to the development of computingWarren McCulloch(a neurophysiologist) and Walter Pitts(alogician) – in 1943 proposed the first model of an artificial43neuronA cellular automaton – a collection of “colored” cells on agrid that evolves through a number of steps according to a setof rulesAb initio – a Latin term meaning “from the beginning”In silico – is coined as an analogy to the Latin phrases,means “performed on a computer or via a computersimulation”A priori – a Latin expression meaning “the truth independentof experience”DNA – deoxyribonucleic acid, a molecule that encodes thegenetic instructionsHamiltonian Graph Problem – comes from graph theory, it isa special case of a travelling salesman problemSierpinski triangle – a fractal with a shape of an equilateraltriangle, subdivided into smaller equilateral trianglesIn vivo – a Latin term, means “experimentation using awhole living organism”E.Coli – a rod-shaped bacterium constituting about 0.1% ofgut floraExercises1.Give Russian equivalents to the following words and phrasesand explain them in your own words:Robustness; the former...the latter; nature-inspired models; tostudy extensively; to draw the inspiration from...; to gainmomentum; to be referred to as...; combinatorialoptimization problems; to perform...

in a highly parallelfashion; a distinction between self and nonself cells; thepioneers of artificial life; a nested hierarchical structure; amembrane enveloped region; a breakthrough experiment; theWatson-Crick complementarity binding; a computationalinsight into some fundamental issues.2. Translate the sentences into Russian paying attention toprefixes and suffixes:1. Despite the relentless, breathtaking advances in computing44and related technologies, we continue to be humbled by thevariety, adaptability, and sophistication of the natural worldaround us.2.

Biologically inspired computing is a field that linksvarious disciplines such as artificial intelligence, evolutionarycomputation, biorobotics, artificial life, and agent-basedsystems.3. Natural computing is a highly interdisciplinary field thatconnects the natural sciences with computing science.4. Genetic algorithms are today modified heavily forapplications to real-valued parameter optimization problemsas well as permutation-based problems.5. Particle Swarm Optimization algorithms have been used tosolve various optimization problems, and have been appliedto unsupervised learning.6. Physical robots were materializations of their virtuallyevolved computational counterparts.7. The field of Artificial Life continues to explore directionssuch as artificial chemistry, as well as traditionally-biologicalphenomena in artificial systems, ranging from coevolutionary adaptation and development to growth, selfreplication, and self-repair.8.

A generic membrane system is essentially a nestedhierarchical structure of cell-like compartments or regions,delimited by “membranes”.9. There are many possible DNA bio-operations that one canuse for computations, such as: cut-and-paste operationsachievable by enzymes, synthesizing desired DNA strands upto a certain length, making exponentially many copies of aDNA strand, and reading-out the sequence of a DNA strand.3. Give English equivalents to the following words andphrases:...Увеличивалось разделение; в сущности...; подробноизучать; параметры, принимающие действительныезначения; составление расписания; непредвиденныеизменения; распознавание своих и не своих клеток;45цепочки ДНК; самый заметный; самосборные структуры;впоследствии; оттеснять на второй план; составныечасти; правдоподобная гипотеза; скрупулезный; быстровпитывать идеи.4.

Answer the following questions:1. What does biologically inspired computing investigate?2. What are the three branches of evolutionary system andwhat are their modern applications?3. How can swarm intelligence contribute to the developmentof unsupervised learning?4. Why is it possible to use amorphous computing as a basisof “cellular computing”?5. What ideas underlie the development of molecularcomputing?6. How does molecular computing contribute to the researchin nanosciences, namely, self-assembly?7. What are the possible quantum computer applications?8. What are the chief similarities and differences betweengenomic computer and an electronic computer?9. Is there a principal difference between systems biologyand synthetic biology in terms of biological systems study?5.

Translate from Russian into English:Эволюционные вычисления, синонимом которых взарубежной литературе является термин «evolutionarycomputation», доказали свою эффективность как прирешении трудноформализуемых задач искусственногоинтеллекта (распознавание образов, кластеризация,ассоциативный поиск), так и при решении трудоемкихзадач оптимизации, аппроксимации, интеллектуальнойобработки данных. К преимуществам эволюционныхвычислений относятся адаптивность, способность кобучению,параллелизм,возможностьпостроениягибридныхинтеллектуальныхсистемнаосновекомбинированияспарадигмамиискусственныхнейросетей и нечеткой логики. Многообещающей46выглядит предпосылка создания единой концепцииэволюционных вычислений, включающих генетическиеалгоритмы,генетическоепрограммирование,эволюционныестратегиииэволюционноепрограммирование.

По мнению многих исследователей,этипарадигмыявляютсяаналогамипроцессов,происходящих в живой природе и на практикедоказавших свою непримитивность.Один из пионеров эволюционных вычислений Л.Фогельвообще видит теорию эволюции и самоорганизации какбазовуюконцепциюдлявсехинтеллектуальныхпроцессов и систем, значительно расширяющую сферуприменения традиционной парадигмы искусственногоинтеллекта.

Даже если это не так, и в природепроисходит реэволюция, никто не может сказать, чтоалгоритмыэволюционных вычислений неверны.6. Summarize the text and express your own opinion. Hereare some possible statements to support:1. A closer look at nature from the point of view ofinformation processing can and will change what we mean bycomputation.2.

Bio-inspired algorithms can exhibit strength throughflexibility: they often work well even when the desired task ispoorely defined, adapt to unforeseen changes in the taskenvironment, or achieve global behavior through interactionamong many, simply programmed agents.3. Ant algorithms are used to solve mainly combinatorialoptimization problems defined over discrete search spaces.4. So far, the theory of quantum computing has been farmore developed than the practice.5.