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87
From Boolean to Probabilistic Boolean Networks as Models of Genetic Regulatory Networks
 Proc. IEEE
, 2002
"... Mathematical and computational modeling of genetic regulatory networks promises to uncover the fundamental principles governing biological systems in an integrarive and holistic manner. It also paves the way toward the development of systematic approaches for effective therapeutic intervention in di ..."
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Cited by 82 (16 self)
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Mathematical and computational modeling of genetic regulatory networks promises to uncover the fundamental principles governing biological systems in an integrarive and holistic manner. It also paves the way toward the development of systematic approaches for effective therapeutic intervention in disease. The central theme in this paper is the Boolean formalism as a building block for modeling complex, largescale, and dynamical networks of genetic interactions. We discuss the goals of modeling genetic networks as well as the data requirements. The Boolean formalism is justified from several points of view. We then introduce Boolean networks and discuss their relationships to nonlinear digital filters. The role of Boolean networks in understanding cell differentiation and cellular functional states is discussed. The inference of Boolean networks from real gene expression data is considered from the viewpoints of computational learning theory and nonlinear signal processing, touching on computational complexity of learning and robustness. Then, a discussion of the need to handle uncertainty in a probabilistic framework is presented, leading to an introduction of probabilistic Boolean networks and their relationships to Markov chains. Methods for quantifying the influence of genes on other genes are presented. The general question of the potential effect of individual genes on the global dynamical network behavior is considered using stochastic perturbation analysis. This discussion then leads into the problem of target identification for therapeutic intervention via the development of several computational tools based on firstpassage times in Markov chains. Examples from biology are presented throughout the paper. 1
Statistical physics of vehicular traffic and some related systems
 PHYSICS REPORT 329
, 2000
"... ..."
Special Purpose Parallel Computing
 Lectures on Parallel Computation
, 1993
"... A vast amount of work has been done in recent years on the design, analysis, implementation and verification of special purpose parallel computing systems. This paper presents a survey of various aspects of this work. A long, but by no means complete, bibliography is given. 1. Introduction Turing ..."
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Cited by 77 (5 self)
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A vast amount of work has been done in recent years on the design, analysis, implementation and verification of special purpose parallel computing systems. This paper presents a survey of various aspects of this work. A long, but by no means complete, bibliography is given. 1. Introduction Turing [365] demonstrated that, in principle, a single general purpose sequential machine could be designed which would be capable of efficiently performing any computation which could be performed by a special purpose sequential machine. The importance of this universality result for subsequent practical developments in computing cannot be overstated. It showed that, for a given computational problem, the additional efficiency advantages which could be gained by designing a special purpose sequential machine for that problem would not be great. Around 1944, von Neumann produced a proposal [66, 389] for a general purpose storedprogram sequential computer which captured the fundamental principles of...
A brief history of cellular automata
, 2000
"... Cellular automata are simple models of computation which exhibit fascinatingly complex behavior. They have captured the attention of several generations of researchers, leading to an extensive body of work. Here we trace a history of cellular automata from their beginnings with von Neumann to the pr ..."
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Cited by 46 (2 self)
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Cellular automata are simple models of computation which exhibit fascinatingly complex behavior. They have captured the attention of several generations of researchers, leading to an extensive body of work. Here we trace a history of cellular automata from their beginnings with von Neumann to the present day. The emphasis is mainly on topics closer to computer science and mathematics rather than physics, biology or other applications. The work should be of interest to both new entrants into the field as well as researchers working on particular aspects of cellular automata.
Computation in cellular automata: A selected review
 Nonstandard Computation
, 1996
"... Cellular automata (CAs) are decentralized spatially extended systems consisting of large numbers of simple identical components with local connectivity. Such systems have the potential to perform complex computations with a high degree of efficiency and robustness, as well as to model the behavior o ..."
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Cited by 33 (2 self)
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Cellular automata (CAs) are decentralized spatially extended systems consisting of large numbers of simple identical components with local connectivity. Such systems have the potential to perform complex computations with a high degree of efficiency and robustness, as well as to model the behavior of complex systems in nature. For these reasons CAs and related architectures have
Emergence of selfreplicating structures in a cellular automata space
 Physica D
, 1997
"... Past cellular automata models of selfreplication have always been initialized with an original copy of the structure that will replicate, and have been based on a transition function that only works for a single, specific structure. This article demonstrates for the first time that it is possible t ..."
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Cited by 30 (5 self)
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Past cellular automata models of selfreplication have always been initialized with an original copy of the structure that will replicate, and have been based on a transition function that only works for a single, specific structure. This article demonstrates for the first time that it is possible to create cellular automata models in which a selfreplicating structure emerges from an initial state having a random density and distribution of individual components. These emergent selfreplicating structures employ a fairly general rule set that can support the replication of structures of different sizes and their growth from smaller to larger ones. This rule set also allows "random " interactions of selfreplicating structures with each other and with other structures within the cellular automata space. Systematic simulations show that emergence and growth of replicants occurs often and is essentially independent of the cellular space size, initial random pattern of components, and initial density of components, over a broad range of these parameters. The number of replicants and the total number of components they incorporate generally approach quasistable values with time.
A New SelfReproducing Cellular Automaton Capable of Construction and Computation
 in ECAL95: Proceedings of the Third European Conference on Artificial
, 1995
"... We present a new selfreproducing cellular automaton capable of construction and computation beyond selfreproduction. Our automaton makes use of some of the concepts developed by Langton for his selfreproducing automaton, but provides the added advantage of being able to perform independent constr ..."
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Cited by 30 (7 self)
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We present a new selfreproducing cellular automaton capable of construction and computation beyond selfreproduction. Our automaton makes use of some of the concepts developed by Langton for his selfreproducing automaton, but provides the added advantage of being able to perform independent constructional and computational tasks alongside selfreproduction. Our automaton is capable, like Langton's automaton and with comparable complexity, of simple selfreplication, but it also provides (at the cost, naturally, of increased complexity) the option of attaching to the automaton an executable program which will be duplicated and executed in each of the copies of the automaton. After describing in some detail the selfreproduction mechanism of our automaton, we provide a nontrivial example of its constructional capabilities. 1 Introduction The history of selfreproducing cellular automata basically begins with John von Neumann's research in the field of complex selfreproducing machi...
An Implementation of von Neumann's SelfReproducing Machine
 Artificial Life
, 1996
"... This article describes in detail an implementation of John von Neumann's selfreproducing machine. Selfreproduction is achieved as a special case of construction by a universal constructor. The theoretical proof of the existence of such machines was given by John von Neumann in the early 1950s ..."
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Cited by 29 (0 self)
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This article describes in detail an implementation of John von Neumann's selfreproducing machine. Selfreproduction is achieved as a special case of construction by a universal constructor. The theoretical proof of the existence of such machines was given by John von Neumann in the early 1950s [6], but was first implemented in 1994, by the author in collaboration with R. Nobili. Our implementation relies on an extension of the statetransition rule of von Neumann's original cellular automaton. This extension was introduced to simplify the design of the constructor. The main operations in our constructor can be mapped into operations of von Neumann's machine. 1 Introduction Von Neumann [6] introduced constructive universality in cellular automata to study the implementability of selfreproducing machines and to extend the concept of computational universality, introduced by A. Turing [5]. A computing machine is said to be computationally universal if it is capable of simu...
A SelfRepairing MultiplexerBased FPGA Inspired by Biological Processes
, 1998
"... Biological organisms are among the most robust systems known to man. Their robustness is based on a set of processes which cannot be adapted directly to the world of silicon, but can provide an inspiration for the design of robust circuits. This paper introduces a multiplexerbased FPGA which we made ..."
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Cited by 29 (18 self)
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Biological organisms are among the most robust systems known to man. Their robustness is based on a set of processes which cannot be adapted directly to the world of silicon, but can provide an inspiration for the design of robust circuits. This paper introduces a multiplexerbased FPGA which we made capable of selftest and selfrepair using an approach loosely based on biological mechanisms at the cellular level. The system is designed to provide online selftest and selfrepair using a completely distributed system and a minimal amount of additional logic. 1.