ライフサイエンスコーパス: heuristic

1 ined from GenBank metadata (i.e. a 'metadata heuristic').

2 iders per vehicle (optimally) or three (with heuristics).

3 lows us to employ the effective beam pruning heuristic.

4 an inherited yet highly accurate behavioural heuristic.

5 ality can emerge from a simple physiological heuristic.

6 ter than those found by the widely-used Jane heuristic.

7 reputation are also observed to support this heuristic.

8 -ended, intuitions supplied by the inherence heuristic.

9 explaining this fact requires the inherence heuristic.

10 en proposed for large networks, some of them heuristic.

11 ion-making tasks based on a linear threshold heuristic.

12 pposed to using some manifestly non-Bayesian heuristic.

13 and the birds-of-a-feather friendship choice heuristic.

14 are less likely to switch to pro-cooperative heuristics.

15 gmenting characters without CAPTCHA-specific heuristics.

16 tly assigned to predicted target genes using heuristics.

17 xed strategy agents with static behaviors or heuristics.

18 ms and their phonetic realizations defy such heuristics.

19 logistic regression modeling, and additional heuristics.

20 imize gains but often result in poor quality heuristics.

21 dressed cursorily and at times using various heuristics.

22 ore accurate and precise than those based on heuristics.

23 NP-hard, restricting practical approaches to heuristics.

24 ing one random or "best" hit based on simple heuristics.

25 lectrophysiology protocols and global search heuristics.

26 encourage the use of formally less competent heuristics.

27 airport perimeters, or with dynamical ad hoc heuristics.

28 r each drug-target pair and outperform other heuristics.

29 d to previously published linear-time greedy heuristics.

30 with bounded capacity using close-to-optimal heuristics.

31 r that behavior is actually achieved through heuristics.

32 alternative schedules determined by several heuristics.

33 our system performed best using the metadata heuristic (0.54 Precision, 0.89 Recall and 0.68 F-score)

34 t to a variety of human cognitive biases(1), heuristics(2) and social influences(3).

35 location disambiguation including a distance heuristic, a population heuristic and a novel heuristic

36 model shows how homophily as a friend-choice heuristic affects the network structure: (1) homophilic

37 phylogenetic tree topologies than the kmacs heuristic algorithm at highly competitive speed.

38 Our results suggest that our greedy heuristic algorithm not only works well but also outperf

39 In addition, we introduce a heuristic algorithm that efficiently identifies high-qua

40 Here, we describe a heuristic algorithm that uses a k-mer-based approach to

41 e trade-off optimization model and develop a heuristic algorithm to obtain the optimal trade-off topo

42 linear time, we design a similar linear-time heuristic algorithm, LinearPartition, to approximate the

43 e that this problem is NP-hard and develop a heuristic algorithm, Revealing Evolutionary Consensus Ac

44 ng callers with complementary strengths by a heuristic algorithm; (c) re-genotypes each CNVR with loc

45 ermines apparent false positives inferred by heuristic algorithms especially among proteomes recovere

46 Based on image-segmentation and heuristic algorithms for object tracking, the software a

47 (Unified Medical Language System(R)) and on heuristic algorithms for parsing data.

48 m of computational complexity, a plethora of heuristic algorithms have arisen that report a 'good eno

49 We propose two heuristic algorithms, H-PoP and H-PoPG, based on dynamic

50 rd' Vargas alignments can be used to improve heuristic alignment accuracy by optimizing command-line

51 A-align lies at the quick convergence of the heuristic alignment iterations and the coarse-grained se

52 at essentialism can do without the inherence heuristic altogether.

53 Here, we present the Haystack Heuristic, an algorithm customized to computationally ex

54 including a distance heuristic, a population heuristic and a novel heuristic utilizing knowledge obta

55 lines are inherently flawed by the anchoring heuristic and efforts should center on decreasing exposu

56 Although GUM is a predictive heuristic and may not be necessarily reflective of the a

57 as not attributable to a win-stay-lose-shift heuristic and reversed as the environmental richness inc

58 the brain implements this important decision heuristic and what underlies individual differences have

59 it highly desirable to search for efficient heuristics and algorithms to, at least, partially answer

60 define sequence similarity based on various heuristics and can only provide rough approximations to

61 er than several alternatives based on simple heuristics and deep neural networks.

62 imension reduction, t-SNE, requires multiple heuristics and fails to produce clear representations of

63 s found to be poor, leading to the view that heuristics and prior assumptions are critical for 3D mot

64 ions, discerning between innate, model-free, heuristic, and model-based controllers.

65 The win-stay/lose-shift heuristic appears not to be a unified mechanism, with th

66 m textual metadata and GEO data using both a heuristic approach as well as machine learning.

67 We show together with a heuristic approach it provides a simple solution for the

68 l Maximum by Convex hull (OLMC), that uses a heuristic approach to estimate the required parameters b

69 genome sequencing project and a phylogenetic heuristic approach to show that reassortment, a reticula

70 re optimal results than the results from the heuristic approach, and is significantly faster.

71 erformance over utilizing only uni-reads and heuristic approaches aimed at rescuing multi-reads on be

72 Many analyses of Ribo-Seq data have utilized heuristic approaches applied to a narrow range of fragme

73 means that developing general principles and heuristic approaches is important.

74 Unlike the heuristic approaches that attempt to predict enzyme stab

75 ltammetry and data optimization methods over heuristic approaches to "experiment"-theory comparisons

76 number of seeds compared with other scalable heuristic approaches.

77 g studies, which have mostly relied on novel heuristic approaches.

78 ximated more simply by human observers using heuristic approaches.

79 these optimal goals can be achieved through heuristic approximation.

80 ength of the input sequence, and thus greedy heuristics are applied to speed up the extension.

81 reas higher level skills, such as the use of heuristics, are taught at postgraduate level.

82 Contrary to widespread belief based on heuristic arguments of genetic relatedness, non-reproduc

83 functional forms are largely justified with heuristic arguments.

84 aracterization of a domain-general inherence heuristic, available to young children, underplays the i

85 onservations, using a novel alignment search heuristic based on integer programming and Lagrangian re

86 ding global compaction that are derived from heuristics based on amino acid compositions for IDRs wit

87 rs of putative homologous genes recovered by heuristic-based approaches.

88 ourced labels were 94.5% concordant with the heuristic-based draft benchmark SV callset from GIAB.

89 l is selected from the CB513 dataset using a heuristics-based approach.

90 een explained through rationality as well as heuristics-based models.

91 thermo-mechanical pathways of biodamage, and heuristic biological criteria for cell survival.

92 we confirm the potential of 18F-AV-1451 as a heuristic biomarker, but caution is indicated in the neu

93 o use the Bayes optimal strategy or to use a heuristic but suboptimal strategy.

94 While those algorithms are heuristic by necessity and should be used with strict se

95 We develop a heuristic called DOCKS to find a compact UHS, which work

96 Fortunately, the same heuristic can also be used to identify reliable targets

97 We show that simple chemical heuristics can be a powerful tool to characterize topolo

98 natorial approaches led by genetic algorithm heuristics can enable identification of active additive

99 uristics to accelerate processing, but these heuristics can fail to find the optimal alignments of re

100 Simulating graph models, we identify a heuristic cellular division rule that reproduces the obs

101 h smaller than the one predicted by previous heuristic centralities.

102 for formal selection by exposing how common heuristic choices, which seem sensible, can be misleadin

103 ood performance using computationally faster heuristic clustering approaches (e.g. k-means).

104 So far, exact and heuristic coarse-graining methods have been mostly restr

105 We have developed a set of algorithms and heuristics collectively called indelMINER to identify in

106 we tested whether confidence reports reflect heuristic computations (e.g. the magnitude of sensory da

107 ptimal foraging theory, nutritional ecology, heuristics) conceptualise multi-attribute choice and we

108 It may be an example of fast heuristic decision-making, which is adaptive in natural

109 ining data, weak supervision relies on noisy heuristics defined by domain experts to programmatically

110 The second stage uses heuristics derived from a simulation strategy to identif

111 rocesses are typically designed according to heuristics derived from batch experiments in which the i

112 and combines a binary search algorithm with heuristics derived from the Central Limit Theorem.

113 ng straightforward implementations of simple heuristic design rules.

114 ent regulations and with the aim of minimize heuristic efforts associated with analytical method deve

115 top of the existing force scheme, additional heuristics employing new types of forces and movement ru

116 urements or the development of a specialised heuristic, enabling in general the automated generation

117 erally involves time- and resource-intensive heuristic endeavors.

118 Despite numerous heuristic enhancement methods, there is a research gap i

119 Hill's heuristic equation is still used, and the sliding-filame

120 stead programs such as Structure make use of heuristic estimators to approximate this quantity.

121 racterization for a biochemical network is a heuristic evaluation process that produces a characteriz

122 No systematic algorithms or heuristics exist to detect and filter batch effects or r

123 A heuristic explanation of this observation is grounded in

124 ric, mQC, based on a mix of data-derived and heuristic features.

125 Due to only using heuristic filtering based on significance score cutoffs

126 We have previously proposed a mapping heuristic for a subset of bioactivities stored in ChEMBL

127 in biology and materials design and offers a heuristic for ensuring that desired material properties

128 values of individual features can provide a heuristic for estimating reward values of choice options

129 ALFRED-G is an alignment-free heuristic for evolutionary distance estimation between t

130 ed probabilities, ScisTree implements a fast heuristic for inferring cell lineage tree and calling th

131 rtially by personal experiences; an accurate heuristic for local changes in climate identifies obstac

132 by its activation energy) provides a simple heuristic for predicting whether tropical/low-elevation

133 ent Research Tool (SMART), a novel searching heuristic for shotgun metagenomics sequencing results.

134 , we propose a variable neighbourhood search heuristic for the conformational search problem.

135 These studies establish a reliable heuristic for the design of SULT1A3 allosteric inhibitor

136 In this paper we focus on an heuristic for the identification of biomarkers called RG

137 We propose RGIFE, a heuristic for the inference of reduced panels of biomark

138 g geographic gradients provides a convenient heuristic for understanding what drives and maintains di

139 degree network nodes and the application of heuristics for both structural and affective information

140 contrast-relationships can serve as powerful heuristics for face detection.

141 s related to phylogeography using integrated heuristics for location disambiguation including a dista

142 ediction efforts have relied on a variety of heuristics for the choice of negative examples.

143 We use our heuristic formula to suggest a number of observational r

144 A simple, heuristic formula with parallels to the Drake Equation i

145 This heuristic framework allows customization of the material

146 ropose a neuroimmune network hypothesis as a heuristic framework for organizing knowledge from dispar

147 This article proposes a heuristic framework for the Addictions Neuroclinical Ass

148 We propose a heuristic framework that divides formation of work or ta

149 Using Marr's three levels of analysis as a heuristic framework, we focus on this variable behaviour

150 Vargas implements a heuristic-free algorithm guaranteed to find the highest-

151 y using a previously published curve-fitting heuristic from the relationship between pressure reactiv

152 he idea that control is recruited to prevent heuristics from producing biased choices, the right infe

153 Such context-dependent heuristic-guided foraging enables optimal, suboptimal, o

154 , i.e., a similarity-based friendship choice heuristic, has been shown to be the main factor in selec

155 These heuristics, however, usually only apply to pairwise sequ

156 emonstrate the effectiveness of the Haystack Heuristic in computing possible biomarker candidates fro

157 rds and that they abstained from some simple heuristics in assessment of the alternative paths, such

158 with the GRAPPA framework, outperforms other heuristics in terms of accuracy, while also continuing t

159 uristics that get replaced by better adapted heuristics in the long run.

160 find further marginal improvements using two heuristics informed by known results in graph theory tha

161 These visualization methods provide heuristic insight into why individual neurons or network

162 are consistent with a combination of simple heuristics involving early-spending, spreading or saving

163 using real sequence datasets shows that our heuristic is able to reconstruct comparable, or even mor

164 One pervasive and powerful heuristic is aversive pruning, in which potential decisi

165 This heuristic is found to be implicitly present in the curre

166 The use of heuristics is motivated by showing the NP-hardness of a

167 open-source software tool that implements a heuristic iterated glycan sequencing algorithm coupled w

168 other and identify gaps between research and heuristic knowledge.

169 th the animal's tendency to deviate from the heuristic learning algorithm.

170 This seed-and-extend heuristic makes BLAST extremely fast and has led to its

171 With the aid of a heuristic mathematical model, we postulate that if the r

172 In this perspective, with the aid of heuristic mathematical-computer simulation models, we ex

173 Time-based heuristic mechanisms were related to activity in sensori

174 Here, we describe StanDep, a novel heuristic method for using transcriptomics to identify c

175 atisfying solutions for NSP and suggests the heuristic method is potentially achievable for practical

176 e Photonic Recurrent Ising Sampler (PRIS), a heuristic method tailored for parallel architectures all

177 We further developed a three-step heuristic method to automate the interpretation of the B

178 We propose a heuristic method to detect potentially misclassified tax

179 Quantum annealing is a promising heuristic method to solve combinatorial optimization pro

180 A heuristic method was proposed to solve this problem.

181 We propose a new heuristic method, MULTIRES, to reconstruct ancestral gen

182 ap in maximizing network resilience: current heuristic methods are designed to immunize vital nodes o

183 Heuristic methods are often employed for quality control

184 nd spreading dynamics, leaving space only to heuristic methods based on the drastic approximation of

185 In contrast to heuristic methods evaluating nodes' significance separat

186 While numerous heuristic methods exist that successfully pinpoint disea

187 ic test of the performance of a multitude of heuristic methods for the identification of influential

188 benchmark the experiment with bootstrapping heuristic methods scaling polynomially with the system s

189 Our work suggests speedups in heuristic methods via photonic implementations of the PR

190 es better accuracy than previously published heuristic methods, while being comparable in its applica

191 e) constraint programming is used instead of heuristic methods.

192 and scalability to the fastest, score-based heuristic methods.

193 eplicates (POA), was compared with two other heuristics methods (WOA and GOA).

194 rive the 'persistence potential': a general, heuristic metric that predicts the persistence and abund

195 mulated trajectories is shown to represent a heuristic mimicking FSM.

196 The proposed heuristic model captures observed global trends of bacte

197 We also describe a simple heuristic model for predicting UGT-mediated sites of met

198 We present a heuristic model for the different growth stages of the C

199 Lane et al. propose a heuristic model in which distinct, and seemingly irrecon

200 oral and clinical neuroscience, we propose a heuristic model in which reduced NMDAR function may indu

201 This is shown with a heuristic model of network dynamics that incorporates ou

202 mood disorders was synthesized to describe a heuristic model of perimenopausal depression development

203 Using a heuristic model of tropical rainfall distribution, we pr

204 The authors' heuristic model suggests that for some women, failure of

205 llows us to propose a simple simulation-free heuristic model that rapidly and accurately predicts the

206 We use a heuristic model to show that this metric is often unacce

207 Neuronal networks are the standard heuristic model today for describing brain activity asso

208 e data were well accounted for by a Bayesian heuristic model, in which the agent continues sampling u

209 Two heuristic models for the tri-exponential decay involving

210 nimize the penalty, through a combination of heuristic Monte Carlo optimization and exact binary quad

211 The authors conclude that the multi-heuristic nature of modern biotechnology makes it an eng

212 A heuristic neurobiological framework for understanding th

213 d on Monte Carlo Markov Chain or alternative heuristics not only offer no such guarantee, but also ar

214 iated with factors that likely represent the heuristics nurses use to assess whether an alarm represe

215 These approaches, however, often optimize a heuristic objective function and require strong assumpti

216 easured directly, rather than relying on the heuristic of board type; this article describes several

217 evidence can be computed exactly-that these heuristics often fail to estimate the true evidence and

218 VOCCluster was created from a heuristic ontology based on the observation of experts u

219 Here, we present HOPS (Heuristic Operations for Pathogen Screening), an automat

220 onfidence in our tasks without necessitating heuristic operations.

221 We establish a heuristic optimisation technique for the design of the m

222 Using a heuristic optimization approach to sentinel selection, t

223 Many decades of heuristic optimization have gone into perfecting convent

224 dels, supported by analytical methods, and a heuristic optimization scheme, we identify a material ge

225 nisms and populations and where we have some heuristic or coarse physical knowledge about states of i

226 tammetric) studies is usually undertaken via heuristic or data optimization comparison of the experim

227 stematic biases that are often attributed to heuristics or limitations in cognitive processes.

228 Lieder & Griffiths without heavy reliance on heuristics or on assumptions of the computational resour

229 e partially accounted for using "compression heuristics", or schemata that simplify the encoding and

230 al multistep crystallization governed by the heuristic "Ostwald's rule of stages", which predicts tha

231 liefs, actually stems from suboptimal neural heuristics over rational beliefs about reward contingenc

232 We anticipate our results will serve as a heuristic paradigm for more sophisticated studies on hem

233 Current interpretation depends on heuristic peak assignments for simple spectra, precludin

234 version of hmmsearch in HMMER 3.x, utilizes heuristic-pipeline which consists of MSV/SSV (Multiple/S

235 y on immediate predator probability-a myopic heuristic policy-and on the optimal policy, which integr

236 vely tuned through stochastic-gradient-based heuristic processes over a cost function.

237 the network alignment problem, aligners are heuristics providing divergent solutions and no consensu

238 to clustering of data points; and are often heuristic, providing an unsatisfactory solution in many

239 These historical metrics provide useful heuristic quality references for experiment across all c

240 current clustering theory relies largely on heuristic rather than mechanistic models.

241 The likelihood that behavior was heuristic rather than normative is suggested by the weak

242 work of experiments and analysis to inform a heuristic reduction of structural sensitivity in a model

243 take into account sensory uncertainty via a heuristic rule.

244 Several heuristic rules identified here can be helpful for discr

245 We capture the role of the linker in a heuristic scaling model, and we find that compression is

246 tron beam signal as feedback, which allows a heuristic search for the optimal wavefront under laser-p

247 In addition, we use a heuristic search that is linear in size of the sparsity

248 IBD detection algorithm that combines a fast heuristic search with accurate coalescent-based likeliho

249 LCA provides heuristic solutions for population number inference, dim

250 f a novel greedy approach with several other heuristic solutions.

251 r-SSR, which finds all SSRs faster than most heuristic SSR identification algorithms in a parallelize

252 These three heuristic stages map onto the dysregulation of functiona

253 Our procedure omits the need for heuristic steps including pseudocount addition or log-tr

254 stem context has been mixed, so we develop a heuristic strategic mathematical model to obtain general

255 Despite the vast use of heuristic strategies to identify influential spreaders,

256 chological processes, and that the inherence heuristic supplies important explanatory frameworks that

257 oximate Bayesian optimality with a switching heuristic that forgoes multiplicative combination of pri

258 We derive a simple and easy-to-interpret heuristic that integrates these factors into a single eq

259 ds developing effective, albeit not optimal, heuristics that are readily-applicable by users of exist

260 nce impractical for large datasets, multiple heuristics that can approximate ACS(k) have been introdu

261 ich exposes experiential learners to climate heuristics that differ from the global average.

262 with exponential worst-case running time or heuristics that do not guarantee optimal solutions.

263 m to avail themselves of many strategies and heuristics that efficiently simplify, approximate, and h

264 In the short run subjects use naive learning heuristics that get replaced by better adapted heuristic

265 lgorithm for RNA folding that is amenable to heuristics that make it run in O(n) time and O(n) space,

266 Here, we propose a descriptor based on the heuristics that structural and energetic 'confusion' obs

267 tegies-from approximately Bayesian to simple heuristics-that the observers may have adopted to update

268 structures of ~80 nucleotides, with minimal heuristics, the complete enumeration of possible seconda

269 The reversibility constraints follow from heuristic thermodynamic poise approximations that take a

270 n this paper, we present a novel linear-time heuristic to approximate ACS(k), which is faster than co

271 timate or reliance on an experiment-specific heuristic to correctly identify and track the motion of

272 It exploits a nodule compactness heuristic to delineate individual nodules.

273 n this algorithm, we have investigated a new heuristic to efficiently compute the lengths of common s

274 Second, rather than posit an inherence heuristic to explain why humans rely more heavily on inh

275 ce tests) were first proposed as an informal heuristic to help assess how "unexpected" the observed e

276 We apply the Haystack Heuristic to nine million B-cell receptor sequences obta

277 tches allowed, and have further applied this heuristic to phylogeny reconstruction.

278 ll number of subsets, and implement a simple heuristic to solve it.

279 Most aligners use heuristics to accelerate processing, but these heuristic

280 available, and practical implementations use heuristics to achieve reasonable runtimes.

281 Furthermore, we provide heuristics to identify, at the proteome level, proteins

282 Therefore, humans frequently use heuristics to reduce the complexity of decisions.

283 t to existing approaches that employ various heuristics to select independent aberrations, RAIG optim

284 While various heuristic tools exist for identifying range shifts and m

285 There are many existing heuristic tools, most commonly based on bidirectional BL

286 Compared with heuristic tools, relevant included models had better dis

287 for the second we propose several efficient heuristics, trading set size for speed and memory.

288 A simple heuristic used in practice is to sample ranks of states

289 erating multiple sequence alignments and its heuristic utility.

290 euristic, a population heuristic and a novel heuristic utilizing knowledge obtained from GenBank meta

291 Addiction models have heuristic value in this regard, because both pain and ad

292 These findings highlight the heuristic value of an integrated functional genomic appr

293 By extending the study of fast-and-frugal heuristics, we view social perceptions as judgment tools

294 In contrast to previous heuristics which either search for exact matches while i

295 Heuristics which implicitly address this problem have em

296 s reputable as oneself emerges as a dominant heuristic, which represents aspirational homophily.

297 repetition algorithms are simple rule-based heuristics with a few hard-coded parameters.

298 of these classifiers using machine learning heuristics with an improved accuracy from Perceptron (81

299 ve way of tackling them is through efficient heuristics with provable performance guarantees, better

300 the design of algorithms may yield practical heuristics with rigorous mathematical justification.