Um algoritmo para comparação sintatica de genomas baseado na complexidade condicional de Kolmogorov

Orientador : João MeidanisDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação CientificaResumo: Desde 1953, quando Natson e Crick desvendaram a estrutura do DNA (ácido desoxirribonucleico), a área de Biologia Molecular tem avançado rapidamente. Técnicas que permitem a manipulação de biomoléculas foram criadas e aperfeiçoadas desde então, gerando enormes quantidades de dados. A necessidade de processar estas informações criou um novo campo chamado de Biologia Molecular Computacional, o qual consiste em desenvolver e usar técnicas matemáticas e de computação para ajudar a resolver problemas de Biologia Molecular. Existem problemas desta área relacionados a Comparação de Genomas, que consiste, a grosso modo, em analisar e comparar seqüências de ácidos nucléicos ou aminoácidos entre espécies. A comparação de genomas busca desvendar as relações existentes entre diferentes espécies. A descoberta de genes ou porções semelhantes nos genomas pode indicar proximidade evolutiva ou regiões indispensáveis à existência da vida. Por outro lado, as diferenças podem relacionar o comportamento particular de uma espécie com uma determinada região de seu genoma. Diante destas observações, iniciamos o desenvolvimento de um algoritmo que realiza a comparação sintática de genomas baseado nos trabalhos de Li e colegas, que utilizam a Complexidade de Kolmogorov para medir a distância entre dois genomas. Ao invés de uma medida de distância, o algoritmo proposto indica as regiões similares entre genomas que são consideradas relevantes pelo critério da Complexidade Condicional de KolmogorovAbstract: Since 1953, when Watson and Crick discovered the DNA (deoxiribonucleic acid) structure, Molecular Biology has advanced quickly. Techniques were developed and improved to manipulate biomolecules since that, generating huge quantities of data. The need to process this information created a new field called Computational Molecular Biology, which consists in the development and usage of mathematical and computing techniques to solve Molecular Biology problems. There are problems in that are a related to Genome Comparison, which consists, roughly speaking, in analysis and comparison of nucleic acid or aminoacid sequences between species. Genome Comparison tries to reveal existing relationships between species. The discovery of similar genes or pieces in genomes can point out evolutionary proximity or indispensable regions for life existence. Besides, differences can relate the unique behavior of a species with some of its genome regions. Based on these observations, we start the development of an algorithm that makes sintatic genome comparison using some ideas of Li and colleagues. They work with Kolmogorov Complexity to measure the distance between two genomes. Instead of a distance measure, the proposed algorithm shows similar regions that are considered relevant by the Conditional Kolmogorov Complexity criteriaMestradoMestre em Ciência da Computaçã

A proof of the Beyer-Stein-Ulam relation between complexity and entropy

AbstractWe present a proof of a conjecture stated by Beyer, Stein and Ulam in 1971. The authors conjectured a relation between Kolmogorov complexity and information entropy

Notes in Pure Mathematics & Mathematical Structures in Physics

These Notes deal with various areas of mathematics, and seek reciprocal combinations, explore mutual relations, ranging from abstract objects to problems in physics.Comment: Small improvements and addition

Computing multi-scale organizations built through assembly

The ability to generate and control assembling structures built over many orders of magnitude is an unsolved challenge of engineering and science. Many of the presumed transformational benefits of nanotechnology and robotics are based directly on this capability. There are still significant theoretical difficulties associated with building such systems, though technology is rapidly ensuring that the tools needed are becoming available in chemical, electronic, and robotic domains. In this thesis a simulated, general-purpose computational prototype is developed which is capable of unlimited assembly and controlled by external input, as well as an additional prototype which, in structures, can emulate any other computing device. These devices are entirely finite-state and distributed in operation. Because of these properties and the unique ability to form unlimited size structures of unlimited computational power, the prototypes represent a novel and useful blueprint on which to base scalable assembly in other domains. A new assembling model of Computational Organization and Regulation over Assembly Levels (CORAL) is also introduced, providing the necessary framework for this investigation. The strict constraints of the CORAL model allow only an assembling unit of a single type, distributed control, and ensure that units cannot be reprogrammed - all reprogramming is done via assembly. Multiple units are instead structured into aggregate computational devices using a procedural or developmental approach. Well-defined comparison of computational power between levels of organization is ensured by the structure of the model. By eliminating ambiguity, the CORAL model provides a pragmatic answer to open questions regarding a framework for hierarchical organization. Finally, a comparison between the designed prototypes and units evolved using evolutionary algorithms is presented as a platform for further research into novel scalable assembly. Evolved units are capable of recursive pairing ability under the control of a signal, a primitive form of unlimited assembly, and do so via symmetry-breaking operations at each step. Heuristic evidence for a required minimal threshold of complexity is provided by the results, and challenges and limitations of the approach are identified for future evolutionary studies

Reading the Texture of Reality : Chaos Theory, Literature and the Humanist Perspective

Tutkimuksessa analysoidaan kaaosteorian vaikutusta kaunokirjallisuudessa ja kirjallisuudentutkimuksessa ja esitetään, että kaaosteorian roolia kirjallisuuden kentällä voidaan parhaiten ymmärtää sen avaamien käsitteiden kautta. Suoran soveltamisen sijaan kaaosteorian avulla on käyty uudenlaisia keskusteluja vanhoista aiheista ja luonnontieteestä ammennetut käsitteet ovat johtaneet aiemmin tukkeutuneiden argumenttien avaamiseen uudesta näkökulmasta käsin. Väitöskirjassa keskitytään kolmeen osa-alueeseen: kaunokirjallisen teoksen rakenteen teoretisointiin, ihmisen (erityisesti tekijän) identiteetin hahmottamiseen ja kuvailemiseen sekä fiktion ja todellisuuden suhteen pohdintaan. Tutkimuksen tarkoituksena on osoittaa, kuinka kaaosteorian kautta näitä aiheita on lähestytty niin kirjallisuustieteessä kuin kaunokirjallisissa teoksissakin. Väitöskirjan keskiössä ovat romaanikirjailija John Barthin, dramatisti Tom Stoppardin ja runoilija Jorie Grahamin teosten analyysit. Nämä kirjailijat ammentavat kaaosteoriasta keinoja käsitteellistää rakenteita, jotka ovat yhtä aikaa dynaamisia prosesseja ja hahmotettavia muotoja. Kaunokirjallisina teemoina nousevat esiin myös ihmisen paradoksaalisesti tunnistettava ja aina muuttuva identiteetti sekä lopullista haltuunottoa pakeneva, mutta silti kiehtova ja tavoiteltava todellisuus. Näiden kirjailijoiden teosten analyysin sekä teoreettisen keskustelun kautta väitöskirjassa tuodaan esiin aiemmassa tutkimuksessa varjoon jäänyt, koherenssia, ymmärrettävyyttä ja realismia painottava humanistinen näkökulma kaaosteorian merkityksestä kirjallisuudessa.Reading the Texture of Reality presents readings of works of fiction, poetry and drama where the concepts developed by chaos theory appear. The study also examines the use of those concepts in literary scholarship and argues that chaos theory is deeply involved in redefining notions central to literary studies, such as literary form, authorial identity and the relation of literature to reality. The study examines the uses of chaos theory in the context of four major theoretical questions: What is literary scholarship and how does it differ from the natural sciences? What is the nature of the literary work and how can it be analysed? What is the relationship between self and other, both in terms of human identity and the different agencies involved in the reading of a literary work? How does the human mind connect to the material universe and how can that universe be represented in literature? All of these questions have been approached by scholars armed with the concepts of chaos theory. The fulcrum of the dissertation is a group of literary works that have clearly been influenced by chaos theory, but which equally clearly fall outside the categories and descriptions suggested by previous theoretical approaches to literature and chaos theory. The emphasis that previous research laid on disorder and uncertainty makes it unable to accommodate works that, while obviously referring to the methods of chaos theory and the systems it studies, also engage the order found in the seemingly complex, the possibility of coherent meaning despite the noise in the message, and the physical reality that lurks behind human sign systems. The discussion focuses on British playwright Tom Stoppard, American novelist John Barth, and American poet Jorie Graham. The issues that their works deal with through chaos theory are similar to those that appear in the works of many of the literary scholars discussed in this study, and thereby make possible a dialogue between literary works and theory. The humanist perspective presented in this study is shown to involve the appreciation of the role of scientific knowledge in culture, the conceptualisation of the literary work as a semi-autonomous and meaningful entity and of human identity as coherence rather than dissolution, as well as the belief that physical reality and embodiment can be represented in literature

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp