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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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Erratum to: “Characterizing chaotic response of a squid axon through generating partitions” [Phys. Lett. A 346 (2005) 141]

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Physics Letters A 2006年第5-6期350卷 429-430页

作者： Yoshito Hirata Kevin Judd Kazuyuki Aihara Centre for Applied Dynamics and Optimization School of Mathematics and Statistics The University of Western Australia 35 Stirling Highway Crawley WA 6009 Australia Department of Mathematical Informatics Graduate School of Information Science and Technology The University of Tokyo Hongo Tokyo 113-8656 Japan ERATO Aihara Complexity Modelling Project JST 45-18 Oyama Shibuya-ku Tokyo 151-0065 Japan

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On the modelling and computation of nonlinear multibody cable systems

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International Journal of Computers and Applications 2006年第2期28卷 154-161页

作者： Fox, B. Jennings, L.S. Zomaya, A.Y. Institute of High Performance Computing Singapore Science Park 2 1 Sci. Pk. Rd. #01-01 The Capricorn 117528 Singapore Singapore Centre of Applied Dynamics and Optimization University of Western Australia Perth WA 6907 Australia School of Information Technologies University of Sydney Madsen Building F09 Sydney NSW 2006 Australia Institute of High Performance Computing Computational Solid Mechanics and Intelligent Engineering Systems Divisions Department of Mathematics University of Western Australia Perth School of Information Technologies University of Sydney

Lagrange's equations of motion are used to obtain a differential algebraic equation representing the nonlinear dynamics of cable systems approximated through the use of multibody modelling. The differential algebraic equation of index 3 is cast as an ordinary differential equation and integrated using the LSODAR software. The cable system consists of an arbitrary number of links between which restoring torques are placed to provide a damping effect. A cable car is introduced to ride upon the cable, where the initial conditions of the cable car system are determined by allowing the original cable system to fall into an equilibrium position. Graphs and animation indicate the chaotic behaviour of both multibody systems, and it is shown that the CPU time increases in a cubic nature as the number of bodies in the system increases. Finally, the accuracy of the results is investigated using a constraint compliance testing procedure.

关键词： Multi agent systems

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Estimating a generating partition from observed time series: Symbolic shadowing

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Physical Review E 2004年第1期70卷 016215-016215页

作者： Yoshito Hirata Kevin Judd Devin Kilminster Centre for Applied Dynamics and Optimization School of Mathematics and Statistics The University of Western Australia 35 Stirling Highway Crawley WA 6009 Australia. yoshito@maths.uwa.edu.au

We propose a deterministic algorithm for approximating a generating partition from a time series using tessellations. Using data generated by Hénon and Ikeda maps, we demonstrate that the proposed method produces partitions that uniquely encode all the periodic points up to some order, and provide good estimates of the metric and topological entropies. The algorithm gives useful results even with a short noisy time series.

关键词： Discrete time control systems

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Estimating topological entropy via a symbolic data compression technique

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Physical Review E 2003年第2期67卷 026205-026205页

作者： Yoshito Hirata Alistair I. Mees Centre for Applied Dynamics and Optimization Department of Mathematics and Statistics The University of Western Australia 35 Stirling Highway Crawley WA 6009 Australia

We estimate topological entropy via symbolic dynamics using a data compression technique called the context-tree weighting method. Unlike other symbolic dynamical approaches, which often have to choose ad hoc parameters such as the depth of a tree, the context-tree weighting method is almost parameter-free and infers the transition structure of the system as well as transition probabilities. Our examples, including a Markov model, the logistic map, and the Hénon map, demonstrate that the convergence is fast: one obtains the theoretically correct topological entropy with a relatively short symbolic sequence.

关键词： Chaos theory

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Modeling continuous processes from data

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Physical Review E 2002年第4期65卷 046704-046704页

作者： Michael Small Kevin Judd Alistair Mees Centre for Applied Dynamics and Optimization Department of Mathematics and Statistics University of Western Australia Perth Australia

Experimental and simulated time series are necessarily discretized in time. However, many real and artificial systems are more naturally modeled as continuous-time systems. This paper reviews the major techniques employed to estimate a continuous vector field from a finite discrete time series. We compare the performance of various methods on experimental and artificial time series and explore the connection between continuous (differential) and discrete (difference equation) systems. As part of this process we propose improvements to existing techniques. Our results demonstrate that the continuous-time dynamics of many noisy data sets can be simulated more accurately by modeling the one-step prediction map than by modeling the vector field. We also show that radial basis models provide superior results to global polynomial models.

关键词： Time series analysis

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Context-tree modeling of observed symbolic dynamics

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Physical Review E 2002年第5期66卷 056209-056209页

作者： Matthew B. Kennel Alistair I. Mees Centre for Applied Dynamics and Optimization The University of Western Australia Nedlands Perth 6907 Western Australia

Modern techniques invented for data compression provide efficient automated algorithms for the modeling of the observed symbolic dynamics. We demonstrate the relationship between coding and modeling, motivating the well-known minimum description length (MDL) principle, and give concrete demonstrations of the “context-tree weighting” and “context-tree maximizing” algorithms. The predictive modeling technique obviates many of the technical difficulties traditionally associated with the correct MDL analyses. These symbolic models, representing the symbol generating process as a finite-state automaton with probabilistic emission probabilities, provide excellent and reliable entropy estimations. The resimulations of estimated tree models satisfying the MDL model-selection criterion are faithful to the original in a number of measures. The modeling suggests that the automated context-tree model construction could replace fixed-order word lengths in many traditional forms of empirical symbolic analysis of the data. We provide an explicit pseudocode for implementation of the context-tree weighting and maximizing algorithms, as well as for the conversion to an equivalent Markov chain.

关键词： Computational complexity

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Context trees and dynamics

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AIP Conference Proceedings 2000年第1期517卷 491-499页

作者： A. I. Mees M. B. Kennel 1Centre for Applied Dynamics and Optimization University of Western Australia Nedlands WA 6907 Australia 2Institute for Nonlinear Science University of California at San Diego La Jolla California 92093

Given a real-world system with behavior which appears complex, it is difficult to separate the effects of chaos, high dimensionality and noise except in the rare cases where a high-quality model is available. Although great progress has been made in modeling such systems, there is little that is rigorous and most algorithms are slow. To gain understanding it seems necessary to idealize in some way, though not, of course, in the traditional way, which is by linearization. In this paper we simplify the problem by assuming that the system outputs symbols from a finite alphabet, rather than outputting a real number. With this simplification and a reasonable assumption which is the discrete analogue of the standard embedding theorem, it is possible to use known results in data compression theory to produce very fast reconstruction algorithms with guaranteed asymptotic optimality. The models that result can be used to simulate and to predict as well as to calculate all the usual dynamically interesting quantities such as topological entropy.

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Detecting periodicity in experimental data using linear modeling techniques

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Physical Review E 1999年第2期59卷 1379-1379页

作者： Michael Small Kevin Judd Centre for Applied Dynamics and Optimization Department of Mathematics and Statistics University of Western Australia Nedlands WA 6907 Australia

Fourier spectral estimates and, to a lesser extent, the autocorrelation function are the primary tools to detect periodicities in experimental data in the physical and biological sciences. We propose a method which is more reliable than traditional techniques, and is able to make clear identification of periodic behavior when traditional techniques do not. This technique is based on an information theoretic reduction of linear (autoregressive) models so that only the essential features of an autoregressive model are retained. These models we call reduced autoregressive models (RARM). The essential features of reduced autoregressive models include any periodicity present in the data. We provide theoretical and numerical evidence from both experimental and artificial data to demonstrate that this technique will reliably detect periodicities if and only if they are present in the data. There are strong information theoretic arguments to support the statement that RARM detects periodicities if they are present. Surrogate data techniques are used to ensure the converse. Furthermore, our calculations demonstrate that RARM is more robust, more accurate, and more sensitive than traditional spectral techniques.

关键词： Time series analysis

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A nonlinear observer for synchronization of chaotic systems

A nonlinear observer for synchronization of chaotic systems

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ASME 1999 Design Engineering Technical Conferences, DETC 1999

作者： Walker, David M. Mees, Alistair I. Department of Applied Science College of William and Mary WilliamsburgVA23187-8795 United States Centre for Applied Dynamics and Optimization University of Western Australia Nedlands PerthWA6907 Australia HP Labs MS4-AD 1501 Page Mill Rd Palo AltoCA94304-1126 United States

ISBN: (纸本)9780791880395

We present a method for the design of nonlinear observers of continuous time chaotic systems. We argue that the synchronization of chaotic systems can usefully be viewed as an observer problem. The method incorporates output feedback, and Lyapunov stability arguments are used to give conditions on whether synchronization is possible. © 1999 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Chaotic systems

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