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Modeling and simulation of genetic regulatory systems: A literature review
 JOURNAL OF COMPUTATIONAL BIOLOGY
, 2002
"... In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between ..."
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Cited by 729 (15 self)
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In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between
A maximum likelihood approach to continuous speech recognition
 IEEE Trans. Pattern Anal. Machine Intell
, 1983
"... AbstractSpeech recognition is formulated as a problem of maximum likelihood decoding. This formulation requires statistical models of the speech production process. In this paper, we describe a number of statistical models for use in speech recognition. We give special attention to determining the ..."
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Cited by 472 (9 self)
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AbstractSpeech recognition is formulated as a problem of maximum likelihood decoding. This formulation requires statistical models of the speech production process. In this paper, we describe a number of statistical models for use in speech recognition. We give special attention to determining
Degree Problems for eNCE Graph Grammars
 Inform. Comput
, 1997
"... The complexity of the bounded degree problem is analyzed for graph languages generated by eNCE graph grammars. In particular, the bounded degree problem is shown to be undecidable for eNCE graph grammars, DEXPTIMEcomplete for confluent/boundary eNCE graph grammars, PSPACEcomplete for linear eNC ..."
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Cited by 2 (2 self)
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The complexity of the bounded degree problem is analyzed for graph languages generated by eNCE graph grammars. In particular, the bounded degree problem is shown to be undecidable for eNCE graph grammars, DEXPTIMEcomplete for confluent/boundary eNCE graph grammars, PSPACEcomplete for linear eNCE
Unsupervised Learning of the Morphology of a Natural Language
 COMPUTATIONAL LINGUISTICS
, 2001
"... This study reports the results of using minimum description length (MDL) analysis to model unsupervised learning of the morphological segmentation of European languages, using corpora ranging in size from 5,000 words to 500,000 words. We develop a set of heuristics that rapidly develop a probabilist ..."
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Cited by 345 (12 self)
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probabilistic morphological grammar, and use MDL as our primary tool to determine whether the modifications proposed by the heuristics will be adopted or not. The resulting grammar matches well the analysis that would be developed by a human morphologist. In the final section, we discuss the relationship
Emptiness problems of eNCE graph languages
 J. of Comp. Syst. Sci
, 1995
"... We consider the complexity of the emptiness problem for various classes of graph languages defined by eNCE (edge label neighborhood controlled embedding) graph grammars. In particular, we show that the emptiness problem is undecidable for general eNCE graph grammars, DEXPTIMEcomplete for conflue ..."
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Cited by 3 (3 self)
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on an exponential time transformation of a confluent eNCE graph grammar into a nonblocking confluent eNCE graph grammar generating the same language. 1 Introduction The theory of graph grammars constitutes a wellmotivated and welldeveloped area within theoretical computer science. The area of graph grammars
Practical Graph Isomorphism
, 1981
"... We develop an improved algorithm for canonically labelling a graph and finding generators for its automorph.ism grou.p. The emphasis i, on th.e power of the algorithm for,01 fling pr4ctical problem.t, rather than on the theoretical n,icetiu of tJu algo rith.m. Th.e nsult is a.n implementa.tion wh.ic ..."
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Cited by 334 (7 self)
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We develop an improved algorithm for canonically labelling a graph and finding generators for its automorph.ism grou.p. The emphasis i, on th.e power of the algorithm for,01 fling pr4ctical problem.t, rather than on the theoretical n,icetiu of tJu algo rith.m. Th.e nsult is a.n implementa.tion wh
The Bounded Degree Problem for nonobstructing eNCE Graph Grammars
"... A graph grammar is called nonobstructing if each graph G derivable from the axiom can derive a terminal graph. In this paper, the bounded degree problem for nonobstructing eNCE graph grammars is proved to be in the complexity class NL. ..."
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A graph grammar is called nonobstructing if each graph G derivable from the axiom can derive a terminal graph. In this paper, the bounded degree problem for nonobstructing eNCE graph grammars is proved to be in the complexity class NL.
The Hierarchical Hidden Markov Model: Analysis and Applications
 MACHINE LEARNING
, 1998
"... . We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our model is motivated by the complex multiscale structure which appears in many natural sequences, particularly in langua ..."
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Cited by 323 (3 self)
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. We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our model is motivated by the complex multiscale structure which appears in many natural sequences, particularly
Attributed ContextFree Hypergraph Grammars
 JOURNAL OF AUTOMATA, LANGUAGES, AND COMBINATORICS
, 1997
"... The concept of contextfree hypergraph grammars (cfhg grammars) has been studied extensively over the past decade. In this paper we introduce attributed contextfree hypergraph grammars (acfhg grammars) as an extension of cfhg grammars. An acfhg grammar consists of an underlying contextfree hypergra ..."
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Cited by 2 (2 self)
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free hypergraph grammar G 0 and an attribution which associates attributes with the nonterminal symbols of G 0 analogous to the classical attribute grammars (ag's) by Knuth. We show that acfhg grammars and ag's are closely related in such a way that an ag can be used to compute the attribute values
Parsing and hypergraphs
 In IWPT
, 2001
"... While symbolic parsers can be viewed as deduction systems, this view is less natural for probabilistic parsers. We present a view of parsing as directed hypergraph analysis which naturally covers both symbolic and probabilistic parsing. We illustrate the approach by showing how a dynamic extension o ..."
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Cited by 77 (3 self)
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While symbolic parsers can be viewed as deduction systems, this view is less natural for probabilistic parsers. We present a view of parsing as directed hypergraph analysis which naturally covers both symbolic and probabilistic parsing. We illustrate the approach by showing how a dynamic extension
Results 1  10
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