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Tytuł artykułu

Artificial intelligence, branching processes and coalescent methods in evolution of humans and early life

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PL
Metody sztucznej inteligencji, procesów gałązkowych i koalescentu w badaniach ewolucji człowieka oraz wczesnego życia
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EN
The book is composed of two parts, which are preceded by the introduction given in Chapter 1, The introduction presents the genesis of problems considered in the monograph, as well as its organization and objectives. Based on these objectives the main problems discussed in the dissertation are formulated. Part I, which is as a presentation of methodological apparatus used in the research studies performed by the author, consists of two chapters, Chapter 2 concerning artificial intelligence, and Chapter 3 related to population genetics. Part II shows how the methods described in Part I are applied in author's evolutionary genetics studies. These studies are roughly focused in three areas, the neutral theory of evolution described in Chapter 4, the evolution of humans discussed in Chapter 5, and the origin of life, considered in Chapter 6. The more specific description of particular chapters is given below. The organization of Chapter 2 is motivated by the natural discrimination between the methods which are inspired by biology, such as artificial neural networks and evolutionary computation, and methods based on formal logie, such as rule-based information systems. It is author's full responsibility that out of many currently studied machine learning methods, he has subjectively chosen in his research neural and evolving systems as those which had arisen from contemplation of life and the rough set theory as the formal logic-based method. However, after this choice has been done and reflected in his studies, the composition of Chapter 2 could not be different. That is also an explanation why the last section in this chapter is a case study - its goal is to illustrate how in one practical application, all these three approaches have found their place. Chapter 3 is a brief presentation of population genetics models, which are used, in addition to machine learning and computer simulations, in author's studies considered in Part II. Comparing the content of this chapter with what is classically understood as a population genetics, the reader will notice that except typical material, such as the Wright-Fisher model of a genetic drift, drift-mutation-selection interplay, and the coalescent method, the chapter also contains a section about genealogy of branching processes. This latter is again the subjective choice, which has been made before writing of the book was started. It was made at the time when the author, inspired by an excellent Kimmel's and Axelrod's book, has introduced to population genetics-related research the branching processes models, in particular the 0'Connell model of branching processes genealogy. Chapter 4, entitled "Theory of Neutral Evolution", after presenting introductory material concerning Kimura's theory of neutral molecular evolution and its relation to the Darwinian selection-driven evolution, focuses on how this theory can be used in search for signatures of natural selection at molecular level. The neutrality tests, which have been designed for detection of such selection are presented, before the case study on that issue is given. The problems with interpretation of the results are the starting point for development of two author's methods: multi-null-hypotheses method and the machine learning-based quasi dominant rough set approach. In Chapter 5, the human evolution is the central point. Within this field many approaches are used for inferring the past of our species, including paleontology and evolutionary genetics. On the background of two competing theories of modern human origin, the multiregional and the recent out-of-Africa hypotheses, there are presented studies concerning detection of past population expansion using classical and author's neural network-based tests. This material is followed by reporting on the research concerning the mitochondrial DNA record. In particular, it is shown how the date of the root of mitochondrial DNA polymorphism is estimated using the 0'Connell and the Wright-Fisher models in forward-time computer simulations of slightly supercritical branching processes. Additionally, in Chapter 5 it is demonstrated how the criticality of branching processes has been used for modeling the decay of hypothetical admixture of Neanderthal mitochondrial DNA in a gene pool of the Upper Paleolithic anatomically modern humans. This issue is currenfly hot debated in the light of results from the Neandertal Genome Project and discussions about interbreeding between H. sapiens and H. neanderthalensis. As Chapter 5 was focused on evolution, which took place less than million years ago, the Chapter 6 speculates about the times almost as ancient as the age of Earth. The point of gravity of Chapter 6 is computer science contribution to the problem of how life has emerged. With that regard, three models are discussed. The first is the Demetrius-Kimmel complexity threshold model supplemented by the author to include hydrolysis of RNA strands caused by phosphodiester bond break reaction. The second is the modification of the Niesert compartment model with random segregation of genetic material. The third is the Monte-Carlo model proposed by Ma and collaborators in 2007, and supplemented by simulation of non-enzymatic template-based RNA recombination process, which seemed to be significant in the emergence of the RNA World. Finally, these three application-oriented chapters which constitute Part JJ of the book, are followed by Chapter 7, which gives the opportunity, not only to summarize the issues discussed in the whole monograph, but also to go beyond that material, by speculating on philosophical matters, which naturally occur when the artificial intelligence is considered.
PL
Niniejsza monografia składa się z dwóch części, które są poprzedzone wstępem zawartym w rozdziale 1. We wprowadzeniu przedstawiono genezę problemów rozważanych w monografii, jak również jej organizację oraz cele. Na podstawie tych celów zostały sformułowane główne problemy rozprawy. Część I, będąca prezentacją aparatu metodologicznego wykorzystywanego w badaniach naukowych autora, składa się z dwóch rozdziałów: rozdziału 2 dotyczącego sztucznej inteligencji i rozdziału 3 na temat genetyki populacyjnej. W części II pokazano, jak metody opisane w części I są wykorzystywane w badaniach prowadzonych przez autora w zakresie genetyki ewolucyjnej. Badania te skupiają się wokół trzech dziedzin: teorii neutralnej ewolucji, opisanej w rozdziale 4, ewolucji człowieka, opisanej w rozdziale 5, oraz pochodzenia życia, rozważanego w rozdziale 6. Bardziej szczegółowy opis poszczególnych rozdziałów znajduje się poniżej. Organizacja rozdziału 2 jest motywowana naturalnym zróżnicowaniem pomiędzy metodami, które są inspirowane przez biologię, takimi jak sztuczne sieci neuronowe i obliczenia ewolucyjne, oraz metodami opartymi na logice formalnej, takimi jak regałowe systemy informacyjne. Autor bierze pełną odpowiedzialność za to, że spośród wielu aktualnie wykorzystywanych metod uczenia maszynowego wybrał w swoich badaniach systemy neuronowe i ewolucyjne jako te, które wyrosły z kontemplacji życia, oraz teorię zbiorów przybliżonych jako metodę opartą na logice formalnej. Jednakże, po dokonaniu tego wyboru odzwierciedlonego w jego badaniach, kompozycja rozdziału 2 nie mogła być już inna. Wybór ten wyjaśnia również, dlaczego ostatnia sekcja tego rozdziału jest poświęcona studium przypadku - jej celem jest zilustrowanie, jak wszystkie te trzy podejścia znajdują swoje miejsca w jednym praktycznym zastosowaniu. Rozdział 3 jest zwartą prezentacją modeli genetyki populacyjnej, które wykorzystywane są, obok uczenia maszynowego i komputerowych symulacji, w badaniach autora rozważanych w części II. Porównując zawartość tego rozdziału z klasycznie ujmowaną genetyką populacyjną czytelnik zauważy, że oprócz typowego materiału, takiego jak model dryfu genetycznego Wrighta-Fishera, współdziałania dryru, mutacji i selekcji oraz metody koalescentu, rozdział zawiera sekcję na temat genealogii procesów gałązkowych. To ostatnie zagadnienie jest znowu subiektywnym wyborem, dokonanym przed rozpoczęciem pisania książki. Decyzja została podjęta, kiedy autor, zainspirowany przez doskonałą książkę Kimmla i Axelroda, wprowadził do swych badań z zakresu genetyki populacyjnej modele procesów gałązkowych, a w szczególności model 0'Connella, dotyczący genealogii procesów gałązkowych. Rozdział 4, zatytułowany "Teoria ewolucji neutralnej", po przedstawieniu materiału wstępnego dotyczącego teorii Kiury, zwanej teorią neutralnej ewolucji molekularnej, jak również jej związków z Darwinowską ewolucją napędzaną przez selekcję, rozważa, jak teoria ta może być wykorzystana w poszukiwaniu znamion selekcji naturalnej na poziomie molekularnym. Pokazano testy neutralności, które zostały zaprojektowane do wykrywania takiej selekcji, a następnie ich wykorzystanie w studium przypadku. Problemy interpretacji rezultatów tych testów stanowiły punkt wyjścia do rozwinięcia dwóch autorskich metod: metody wielu hipotez zerowych oraz metody opartej na uczeniu maszynowym z użyciem podejścia ąuasi-dominujących zbiorów przybliżonych. W rozdziale 5 centralnym punktem jest ewolucja człowieka. W tej dziedzinie zaproponowano wiele podejść, by odkryć przeszłość naszego gatunku, w tej liczbie, metody paleontologiczne i genetyczne. Na tle dwóch konkurujących teorii pochodzenia człowieka współczesnego, hipotezy wieloregionalnej oraz hipotezy pożegnania z Afryką zaprezentowane są badania, mające na celu wykrycie przeszłych okresów ekspansji populacji z wykorzystaniem metod klasycznych, oraz, opartej na sieciach neuronowych, metod autora. Następnie przedstawiono raport z badań na temat zapisu mitochondrialnego DNA. W szczególności pokazano, jak estymowano epokę korzenia polimorfizmu mitochondrialnego DNA z wykorzystaniem modeli 0'Connella oraz Wrighta-Fishera w symulacjach komputerowych lekko nadkrytycznych procesów gałązkowych. Ponadto, w rozdziale 5 pokazano, jak wykorzystać krytyczność procesu gałązkowego do modelowania zaniku hipotetycznej domieszki neandertalskiego mitochondrialnego DNA w puli genów ludzi anatomicznie współczesnych Górnego Paleolitu. Ta kwestia jest aktualnie gorąco dyskutowana w świetle rezultatów Projektu Neandertalskiego Genomu oraz dyskusji na temat krzyżowania pomiędzy H. sapiens i H. Neanderthalensis. O ile rozdział 5 był poświęcony ewolucji działającej w okresie mniej niż milion lat wstecz, rozdział 6 spekuluje na temat czasów prawie tak starych jak sama Ziemia. Punktem ciężkości rozdziału 6 jest wkład informatyki do problemu powstania życia. W tym kontekście są dyskutowane trzy modele. Pierwszy, to model granicy złożoności Demetriusa-Kimmla, uzupełniony przez autora tak, by uwzględniał hydrolizę łańcuchów RNA spowodowaną przez reakcję rozpadu wiązania fosfodiestrowego. Drugi, to modyfikacja kompartmentowego modelu Niesert z losową segregacją materiału genetycznego. Trzeci, to model Monte-Carlo zaproponowany przez Ma i współpracowników w 2007, i uzupełniony przez symulację procesu nieenzymatycznej opartej na wzorcu rekombinacji RNA, który to proces wydaje się być znaczący w powstaniu świata RNA. Na koniec, po tych trzech zorientowanych na zastosowania rozdziałach, które stanowią część II monografii, rozdział 7 stanowi okazję nie tylko do podsumowania problemów poruszanych w całej rozprawie, ale również do wyjścia poza ten materiał poprzez rozważanie kwestii filozoficznych, które naturalnie się pojawiają w myśleniu o sztucznej inteligencji.
Czasopismo
Rocznik
Strony
340--340
Opis fizyczny
s., Bibliogr. 359 poz.
Twórcy
autor
Bibliografia
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