ライフサイエンスコーパス: grammar

1 cluded measures of phonology, semantics, and grammar.

2 by a recursive, self-embedding, context-free grammar.

3 or a text-based Phyletic Pattern Expression grammar.

4 e of a broad coverage syntax-semantic hybrid grammar.

5 hile the learner has to infer the underlying grammar.

6 yntax and semantic information from a single grammar.

7 is enriched dependency structure, as in Word Grammar.

8 s a mathematical description of language and grammar.

9 ge and the biological evolution of universal grammar.

10 ate the sample sentences is called universal grammar.

11 then priming offers no special insight into grammar.

12 he conditions for the evolution of universal grammar.

13 rings generated by an otherwise context-free grammar.

14 that algorithm and a formal transformational grammar.

15 upporting the existence of genes specific to grammar.

16 sts equate knowing a language with knowing a grammar.

17 computation, optimization, for the theory of grammar.

18 learning to process, rather than inducing, a grammar.

19 ammars, learners acquire a single systematic grammar.

20 It is based on a Parsing Expression Grammar.

21 ow the expected productivity of a rule-based grammar.

22 cholinguistic data to processing rather than grammar.

23 tic data (PLD), onto linguistic knowledge, a grammar.

24 with both spatially constrained and flexible grammars.

25 e that monkeys can spontaneously master such grammars.

26 ignments and profile stochastic context-free grammars.

27 uisition which can learn a restricted set of grammars.

28 le CFG synchronized with a number of regular grammars.

29 quisition can only learn a restricted set of grammars.

30 ne grammar out of a limited set of candidate grammars.

31 and competition between different universal grammars.

32 re profiles based on stochastic context-free grammars.

33 both structurally ambiguous and unambiguous grammars.

34 Artificial grammars (AG) are designed to emulate aspects of the str

35 ers novel insights into the relation between grammar and cognition.

36 ection of grammars within the same universal grammar and competition between different universal gram

37 our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for

38 utilizes a specially developed context-free grammar and lexicon.

39 er in nature, with virtually every aspect of grammar and of language affected.

40 language acquisition assume a single target grammar and one PLD source, the central question being w

41 able to classify new patterns defined by the grammar and reliably exclude agrammatical patterns.

42 e problem of discovering and deciphering the grammar and syntax of gene regulation in eukaryotes.

43 a logic grammar formalism called Basic Gene Grammars and a bidirectional chart parser DNA-ChartParse

44 s grammar class encompasses the context-free grammars and goes beyond to generate pseudoknotted struc

45 nces based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF).

46 omputational framework based on context-free grammars and mutual information that systematically expl

47 ations with variation, i.e., multiple target grammars and PLDs.

48 ut more generally to stochastic context free grammars and RNA structure prediction.

49 Basic Gene Grammars and the DNA-ChartParser allowed different sourc

50 Words, grammar, and phonology are linguistically distinct, yet

51 as a valuable tool to those developing phylo-grammars, and as a means for the exploration and dissemi

52 mnesic patients for dot patterns, artificial grammars, and cartoon animals.

53 omain have used full parses, domain-specific grammars, and large knowledge bases encoding domain know

54 tive performance was assessed using implicit grammar- and motor-learning tasks and a detailed neurops

55 l data are directly relevant for determining grammar architecture, we present one main objection to t

56 ov chain substitution models with stochastic grammars, are powerful models for annotating structured

57 How universal grammar arose is a major challenge for evolutionary biol

58 s to explore the suitability of Construction Grammar as an appropriate framework for a schema-based l

59 and sequence lengths were unable to master a grammar at this higher, "phrase structure grammar" level

60 The pseudoknot grammar avoids the use of general context-sensitive rule

61 ient progressive alignment algorithm using a grammar based sequence distance particularly useful in a

62 l to evaluate the explanatory power of child grammars based not on abstract rules but on concrete wor

63 (to facilitate the development of stochastic grammars based on phylogenetic trees, also known as Stat

64 posed progressive alignment algorithm uses a grammar-based distance metric to determine the order in

65 hy of neural processing timescales underlies grammar-based internal construction of hierarchical ling

66 f cross-validation experiments, we show that grammar-based secondary structure prediction methods for

67 ), each learner receives PLD from one target grammar but different learners can have different target

68 is field are expressed using Definite Clause Grammars but these have computational limitations which

69 the probability parameters of the stochastic grammar, but also the instantaneous mutation rates of th

70 he central question being whether the target grammar can be acquired from the PLD.

71 Universal grammar cannot be learned; it must be in place when the

72 tilizing a lexical analyzer and context free grammar (CFG), we demonstrate that efficient parsers can

73 known ncRNA search is based on context-free grammar (CFG), which cannot effectively model pseudoknot

74 We show that context-free grammars (CFG) can formalize these design principles.

75 if, is replaced with a zygotic TSS selection grammar characterized by broader patterns of dinucleotid

76 This grammar class encompasses the context-free grammars and

77 The two TSS-defining grammars coexist, often physically overlapping, in core

78 as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology,

79 f the system was measured by calculating the grammar complexity of the observed sequences, which show

80 contentious, example is whether a universal grammar constrains syntactic diversity in human language

81 tween damage to the frontal aslant tract and grammar deficits suggests that verbal fluency and gramma

82 sentence repetition task was used to assess grammar-dependent verbal working memory, and an auditory

83 on Grammar (TCG), a new form of construction grammar distinguished by its use of SemRep to express se

84 The context-free grammar editor is part of the GenoCAD application.

85 elationships between certain binding sites ("grammar elements") can be identified in all sparkling or

86 identifies key compensatory mechanisms and 'grammar' elements that are critical for maintaining func

87 roof, the library was converted into GenoCAD grammar files to allow users to import and customize the

88 nces under different stochastic context-free grammar folding models.

89 NEMO is recognized by a grammar for transcription network motifs using lex and y

90 rly understood and cannot inform accounts of grammar for two reasons.

91 way to estimate the parameters of stochastic grammars for biological sequence analysis.

92 a new DNA parsing system, comprising a logic grammar formalism called Basic Gene Grammars and a bidir

93 en & Chater (C&C) perspective needs a formal grammar framework capturing word-by-word incrementality,

94 ntitative tests justified the distinction of grammar from speech abnormalities and the desirability o

95 mat) and automated parameterization of those grammars from training data (via the Expectation Maximiz

96 ayesian procedure to extract such item-based grammars from transcriptions of 28+ h of each of two chi

97 A context-free grammar has been developed to model the structure of con

98 ral cognitive capacities, certain aspects of grammar have an autonomous psychological and neural basi

99 While syntax grammars have generally been tested over more documents,

100 ly been tested over more documents, semantic grammars have outperformed them in precision and recall.

101 Despite this profound impairment in grammar, he displayed simple causal reasoning and ToM un

102 language model to understand the underlying grammar, i.e. the arrangement and frequencies of amino a

103 erty of the stimulus" arguments suggest that grammar identification is an intractable inductive probl

104 ial variability regarding this aspect of the grammar, (ii) this variability is attested between speak

105 lant tract in relation to verbal fluency and grammar impairment in primary progressive aphasia.

106 oun" and "verb" represent the basic units of grammar in all human languages, and the retrieval of cat

107 e of mathematical calculations from language grammar in the mature cognitive system.

108 Most formal grammars in this field are expressed using Definite Clau

109 t sequence learning paradigm (an "artificial grammar") in which humans and monkeys were exposed to se

110 r, human language entails more sophisticated grammars, incorporating hierarchical structure.

111 Understanding the nature of protein grammar is critical because amino acid substitutions in

112 ry independently suggests that the choice of grammar is driven in part by a process operating interna

113 The conservation of grammar is examined in seven divergent Drosophila genome

114 who are linguistically homogenous and whose grammar is known to the researcher.

115 Their claim that grammar is merely acquired language processing skill can

116 Formally a context-sensitive grammar is required, which would impose a large increase

117 imum error tolerance for which a predominant grammar is stable.

118 Grammar is the basis of the unlimited expressibility of

119 Grammar is the computational system of language.

120 The use of Basic Gene Grammars is demonstrated in representing many formulatio

121 fy sequences from recursive, centre-embedded grammars is not uniquely human.

122 tside algorithm (for stochastic context-free grammars), is a powerful way to estimate the parameters

123 xposure language is compatible with multiple grammars, learners acquire a single systematic grammar.

124 Artificial grammar learning (AGL) is one of the most extensively em

125 antage for this group was noted for implicit grammar learning (ANOVA, p = 0.021).

126 imuli is the principal feature of artificial grammar learning and prototype learning, then these form

127 d on artificial grammar learning, artificial grammar learning with transfer to novel lettersets, and

128 g, perceptuomotor skill learning, artificial grammar learning, and prototype abstraction; (ii) cortic

129 3 patients with PD were tested on artificial grammar learning, artificial grammar learning with trans

130 l framework for the evolutionary dynamics of grammar learning.

131 the population dynamics of communication and grammar learning.

132 a grammar at this higher, "phrase structure grammar" level.

133 This cis-regulatory "grammar" may aid the identification of enhancers regulat

134 analytical techniques, including a novel MP grammars method to mathematically model putative regulat

135 ar that contrasts with mainstream generative grammar (MGG) in that (a) it treats phonology, syntax, a

136 Technically, the stochastic version of the grammar model can be as simple as an SCFG.

137 We introduce a new grammar modeling approach for RNA pseudoknotted structur

138 Priming implies a network structure, so the grammar must be a network and so must sentence structure

139 to have correctly deciphered the underlying grammar of antimicrobial peptide sequences, as demonstra

140 We conclude that grammar of gene control regions is pervasively used in t

141 Advances include the development of a grammar of graphics, deeper understanding of human perce

142 genomic locations characterized by a unique grammar of homeodomain binding motifs.

143 with positional notation that resembles the grammar of natural languages.

144 ar grammar rather than the context sensitive grammar of the original TOPS model.

145 Children acquire the grammar of their native language without formal educatio

146 ask how accurate children have to learn the grammar of their parents' language for a population of i

147 ealing key differences in the cis-regulatory grammar of these cell types.

148 ns of linguistic theory: What is it that the grammars of all languages share, and how may they differ

149 GBNet is a useful tool for deciphering the "grammar" of transcriptional regulation.

150 Here, we investigate the regulatory 'grammar' of nearly 100 characterized enhancers for devel

151 observed between slow speech with simplified grammar on the one hand, and grammatical and speech soun

152 ally consistent with two possible underlying grammars--one more similar to English in terms of the li

153 We argue that grammar originated as a simplified rule system that evol

154 evaluate the sample sentences and choose one grammar out of a limited set of candidate grammars.

155 The language-based method employed a link grammar parser combined with semantic patterns derived f

156 criptome and that a confluent RFX regulatory grammar plays a significant role in the genetic componen

157 Phylo-grammars, probabilistic models combining Markov chain su

158 ar deficits suggests that verbal fluency and grammar processing rely on distinct anatomical networks.

159 First, those who view performance as grammar + processing will always be able to attribute ps

160 heir selective aspects, including phonology, grammar, prosody and semantics.

161 n's language is consistent with a productive grammar rather than memorization of specific word combin

162 , to give a model characterized by a regular grammar rather than the context sensitive grammar of the

163 ar and logistic mixed models and regression (GRAMMAR), regional heritability mapping (RHM) and haplot

164 eir internal architecture and cis-regulatory grammar remain elusive.

165 obabilistic inferences over a space of graph grammars representing trees, linear orders, multidimensi

166 To investigate more intensively the grammar rules for active regulatory sequence, we made li

167 s successfully using stochastic context-free grammars (SCFG) adapted from computational linguistics;

168 ch (RNAalifold) or a Stochastic Context-Free Grammars (SCFGs) approach (PPfold).

169 More recently, stochastic context-free grammars (SCFGs) have emerged as an alternative probabil

170 Universal grammar specifies the mechanism of language acquisition.

171 Universal grammar specifies the restricted set of languages learna

172 ich consists of a dictionary of motifs and a grammar specifying their usage.

173 d structures based on parallel communicating grammar systems (PCGS).

174 ht, the Iowa gambling task and an artificial grammar task.

175 ion of sentences using Template Construction Grammar (TCG), a new form of construction grammar distin

176 rchitecture, an approach to the structure of grammar that contrasts with mainstream generative gramma

177 terances minimally requires a 'context-free' grammar that is more complex than the 'finite-state' gra

178 We identify one aspect of grammar that varies unpredictably across a population of

179 vors the emergence of rule-based, generative grammars that underlie complex language.

180 gh the use of syntactic rules (or generative grammars) that describe the acceptable structure of utte

181 in the framework of stochastic context-free grammars, that emulates the kinetics of RNA folding in a

182 that is more complex than the 'finite-state' grammars thought sufficient to specify the structure of

183 The model uses a probabilistic grammar to characterize modality-independent representat

184 hich specifies the condition for a universal grammar to induce coherent communication within a popula

185 We used this set of grammars to create new, unnatural AmP sequences.

186 ad, transFold employs multi-tape S-attribute grammars to describe all potential conformations, and th

187 a formal language and built a set of regular grammars to describe this language.

188 We then use these grammars to parse all of the unique multiword utterances

189 n the motifs in order to learn a regulatory 'grammar' to improve predictions.

190 e theory of this restricted set is universal grammar (UG).

191 developed a graphical editor of context-free grammars usable by biologists without prior exposure to

192 des means for the rapid development of phylo-grammars (using a simple file format) and automated para

193 e of generating an infinite set of outputs ("grammars") vary in generative power.

194 pt And XML) web interface to xrate providing grammar visualization tools as well as access to xrate's

195 coordinately regulated genes share a common "grammar," we have examined the distribution of Dorsal re

196 t this with the framework of Universal Moral Grammar, which has sought a descriptively adequate accou

197 in the domains of phonology, semantics, and grammar, which have been closely linked with neuroanatom

198 r graphics platform that combines generative grammars with visual perception, we accessed the mind's

199 We study selection of grammars within the same universal grammar and competiti