ライフサイエンスコーパス: heuristics

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

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

3 optimizations, thereby motivating the use of heuristics.

4 d to previously published linear-time greedy heuristics.

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

6 g the efficient application of hill climbing heuristics.

7 techniques that minimize biases inherent in heuristics.

8 stems have received much less attention than heuristics.

9 current methodologies depend a lot on human heuristics.

10 tools available for analysis of optimization heuristics.

11 m is, in practice, a tractable problem using heuristics.

12 searching algorithm, supplemented with local heuristics.

13 used multiple alignment methods have to use heuristics.

14 opposite or investing in more discriminating heuristics.

15 n of recall by memory failures and cognitive heuristics.

16 r that behavior is actually achieved through heuristics.

17 es by applying physics-inspired optimization heuristics.

18 sing Neighbor-Joining and maximum-likelihood heuristics.

19 ither group average functional maps or scalp heuristics.

20 alternative schedules determined by several heuristics.

21 rast to macroscopically based hydrophobicity heuristics.

22 e and posit to substitute currently employed heuristics.

23 them susceptible to decisional shortcuts, or heuristics.

24 also enable efficient solution by classical heuristics.

25 ndered tractable by ecologically appropriate heuristics.

26 persist as a fundamental component of social heuristics.

27 l-informed sampling compared to using simple heuristics.

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

29 gmenting characters without CAPTCHA-specific heuristics.

30 tly assigned to predicted target genes using heuristics.

31 xed strategy agents with static behaviors or heuristics.

32 ms and their phonetic realizations defy such heuristics.

33 logistic regression modeling, and additional heuristics.

34 imize gains but often result in poor quality heuristics.

35 dressed cursorily and at times using various heuristics.

36 ore accurate and precise than those based on heuristics.

37 NP-hard, restricting practical approaches to heuristics.

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

39 lectrophysiology protocols and global search heuristics.

40 encourage the use of formally less competent heuristics.

41 airport perimeters, or with dynamical ad hoc heuristics.

42 tion algorithms, integer linear programs and heuristics.

43 lect the complexity of domain-specific moral heuristics.

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

45 dollar spent compared with areas selected by heuristics accounting for richness alone or richness and

46 ion of the errors inherent in certain common heuristics alerts clinicians to their weaknesses as diag

47 f our study we defined a set of criteria and heuristics allowing us to automatically build a biologic

48 Based on evolutionary information and heuristics, an Evolutionary Trace Annotation (ETA) pipel

49 It is a mature technique, with the heuristics and accurate E-values required for screening

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

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

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

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

54 n particular, variability in variant calling heuristics and filtering limits the use of current struc

55 Implementation of the criteria as well as heuristics and hardness proofs are available from the au

56 POT also helps researchers develop their own heuristics and incorporate them into the software's grap

57 Our results provide an evidentiary basis for heuristics and learning differences that underlie the fo

58 me lattice into four groups, we use chemical heuristics and local symmetry to explain additional cond

59 uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts;

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

61 d current strategies to address it resort to heuristics and stochastic search techniques.

62 nt flows remain hindered by the inability of heuristics and supervised learning to model the near-wal

63 onsciously might use nudges to exploit these heuristics and thereby influence their patients' decisio

64 hing by evaluation", which heavily relies on heuristics and thus usually yields unreliable contig pat

65 We implemented our heuristics and used them to analyze biological as well a

66 network reconstruction primarily use greedy heuristics and yield sub-optimal solutions.

67 ther model parameters (e.g., decision noise, heuristics), and was specifically related to social diff

68 ce on pre-existing annotations, peak calling heuristics, and collapsing measurements by cell type.

69 undeveloped intuitions, produced by System 1 heuristics, and developed beliefs, constructed by System

70 paths that cut across revealed assumptions, heuristics, and disciplinary boundaries.

71 anism has been challenged by non-integration heuristics, and tracking decision boundaries has proven

72 euristics rely on proxies so the elements of heuristics appear to map well to the elements of proxies

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

74 which are at least as important, 49 creative heuristics are described, divided into 5 categories and

75 cooperation is intuitive because cooperative heuristics are developed in daily life where cooperation

76 Simple heuristics are easy to implement but may be less accurat

77 amount of work specific to tRNAs, where our heuristics are generic to any ncRNA.

78 Cognitive biases and heuristics are systematic errors in thinking that can af

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

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

81 w that their accuracy is usually superior to heuristics based on BLAST.

82 emented with a reference-free genome binning heuristics based on dimension reduction, the proposed me

83 ch social dilemmas, they often employ simple heuristics based on direct reciprocity: cooperate when o

84 Specifically, news consumers form heuristics based on past interactions with warning label

85 Secondly, we apply heuristics-based address clustering to improve the detec

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

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

88 are not appropriate and provide some of the heuristics behind the formulae.

89 d they convert from availability to sampling heuristics between pre-kindergarten and school age.

90 s based on the visual input as well as their heuristics, biases, prior knowledge, and beliefs.

91 refine the existing automation algorithm and heuristics by (1) moving the program to a Python environ

92 -scores outperformed each of the alternative heuristics by 118-213%.

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

94 Key features of our heuristics can be generalized to more complicated protoc

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

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

97 Heuristics can inform human decision making in complex e

98 This suggests that such heuristics can lead to erroneous results.

99 interactions with warning labels, and those heuristics can spill-over into new media environments wh

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

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

102 elligence models that identify environmental heuristics conducive to the growth of pathogenic strains

103 Biases and heuristics contribute to surgical errors and never event

104 e rigorous filters make searches slower than heuristics could be.

105 More uniform use of explicit and better heuristics could lead to less practice variation and mor

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

107 For the former, our numerical heuristics demonstrate the NIBP phenomenon for a realist

108 Furthermore, since choice of the best heuristics depended critically on the properties of (e.g

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

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

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

112 es than our work is dependent on handcrafted heuristics designed for a specific folding model.

113 However, unlike proxy failure, heuristics do not fail because of feedback.

114 c training labels based on predictive global heuristics, dropkick learns a gene-based representation

115 rence heuristic" in a web of domain-specific heuristics (e.g., agent specific; action specific; conse

116 Speeding up this step requires heuristics, efficient implementations, and/or hardware a

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

118 Our splicing heuristics enhance the current framework for genetic var

119 In both cases, our criteria and heuristics exhibited very good performance with respect

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

121 Good software and elaborate heuristics exist, but the process remains laboriously ma

122 tude in execution time the best local search heuristics existing to date when applied to real data.

123 e techniques we describe also provide useful heuristics for assessing relevant properties of sample d

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

125 Existing heuristics for designing water-stable MOFs lack generali

126 ost of these problems are NP-hard, and offer heuristics for efficient and accurate reconstruction of

127 or traits of related organisms, and provide heuristics for experimental design and reconstruction of

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

129 ng transcripts that may not satisfy existing heuristics for gene prediction, we developed a computati

130 mproves upon the run time of standard search heuristics for gene tree parsimony, and enables the firs

131 article, I describe a philosophy and set of heuristics for giving an engaging, narratively driven ta

132 rming function prediction algorithms rely on heuristics for important components of the algorithm, su

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

134 oit low-level spatio-chromatic statistics as heuristics for material judgment.

135 We propose two efficient heuristics for minimizing the number of oligonucleotide

136 stochasticity that is inherent in the use of heuristics for optimizing modularity.

137 Using the Big Five factors as heuristics for organizing the research literature, numer

138 e Journal, Galea and Link identify important heuristics for our discipline.

139 Further, we devise efficient heuristics for parsimony-based reconstruction of phyloge

140 Our findings offer an interesting heuristics for quantum-inspired solvers as well as a pro

141 Here we develop heuristics for reliably detecting gene fusion events in

142 for sensitivity and on PSI-BLAST (and other) heuristics for speed.

143 hat our framework justifies several existing heuristics for task decomposition and makes predictions

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

145 experimentally existing and new local search heuristics for the GTAP using simulated and real data.

146 Further analysis defined simple heuristics for the reliability of connections between br

147 xtraction especially when good normalization heuristics for the target terminology are not fully know

148 ntrolled animal breeding problem and analyse heuristics for two possible objectives: (1) breeding for

149 The interview guide, based on the Usability Heuristics for User Interface Design and the Sociotechni

150 The purpose of our work was to develop heuristics for visualizing and interpreting gene-environ

151 It can also use efficient heuristics from general-purpose ILP solvers to obtain mu

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

153 Through graph-based heuristics, GeD identifies dense subgraphs in the eQTL a

154 Response behaviours were often influenced by heuristics-guided appraisal (i.e. mental rules of thumb)

155 Each of these heuristics has often been used to generate hypotheses in

156 xture graphs can be prohibitively expensive, heuristics have been developed to enable efficient searc

157 A variety of computational heuristics have been developed to pre-emptively identify

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

159 Evidence supporting the social heuristics hypothesis (SHH) suggests that cooperation is

160 The Social Heuristics Hypothesis argues that people with selfish pr

161 We test this 'social heuristics hypothesis' by aggregating across every coope

162 In contrast, consistent with the Social Heuristics Hypothesis, deliberation tends to increase th

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

164 ve as a test for the necessity of confidence heuristics in explaining confidence-accuracy dissociatio

165 Benchmarking against standard serological heuristics in real-world data revealed that serojump ach

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

167 ng that supports the use of image statistics heuristics in the judgement of metallicity-the quality o

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

169 s (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian sett

170 These heuristics include making categorical decisions at the b

171 Computational theories propose different heuristics, including competence measures (e.g., percent

172 ibration step that is built upon data-driven heuristics, including proximity and ratios.

173 istics with those used in tRNAscan-SE, whose heuristics incorporate a significant amount of work spec

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

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

176 Hence, devising efficient network alignment heuristics is currently a foremost challenge in computat

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

178 uced range of resolved scales, have designed heuristics, known as large eddy simulation (LES).

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

180 Instead, ad hoc rules of thumb, or "heuristics," must guide them, and many of these are prob

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

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

183 of this process identified a small number of heuristics of low computational complexity that accounte

184 The heuristics of medicine should be discussed, criticized,

185 the alignment and model to satisfy the known heuristics of protein structure by means of a set of ana

186 es in the sequenced data and assumptions and heuristics of the assemblers.

187 ental suboptimalities arising from ingrained heuristics of the brain.

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

189 nt approaches to fragment assignment rely on heuristics or approximations for tractability.

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

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

192 Five common clinical heuristics or other sources of cognitive error are illus

193 Physicians use heuristics or shortcuts in their decision making to help

194 g Value Imputation Algorithms (MVIAs) employ heuristics or statistical models to replace missing info

195 However, almost all of these methods rely on heuristics or user-supplied parameters to control the nu

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

197 RECENT FINDINGS: Heuristics, or mental shortcuts, allow physicians to mak

198 viduals in such settings may resort to using heuristics, or simplified decision rules, to aid complex

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

200 on in sensorimotor control questions whether heuristics preserve efficiency when actions are nontrivi

201 ulnerable to spoofing(3), in which classical heuristics produce samples, without direct simulation, l

202 as roughly comparable, so we expect that our heuristics provide a high-quality solution that--unlike

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

204 The 49 heuristics range from common sense perceptiveness of the

205 rafted by domain experts and tweaked through heuristics rather than being automatically optimized, pr

206 ility in recovery and a reliance on clinical heuristics rather than empirical methods.

207 social preferences guided by simple decision heuristics, rather than the rational examination of payo

208 Decision-making heuristics rely on proxies so the elements of heuristics

209 d the relative competitiveness of the mating heuristics remains the same.

210 However, the predictive performance of these heuristics remains unknown.

211 Heuristics simplify difficult decisions by ignoring most

212 A variety of computational heuristics, some with a long history, have been proposed

213 take an alternative approach and design LES heuristics stated in terms of Lagrangian particles movin

214 anguage are hindered by intuitive but flawed heuristics such as associating first-person pronouns, us

215 oning and relevant knowledge, and the use of heuristics such as familiarity.

216 hich require several empirical parameters or heuristics such as patterning of residues or rotamers, E

217 abilistic approaches, which can be biased by heuristics such as substring-masking for multiple motif

218 bers of putative ligands; therefore, various heuristics (such as estimation of binding affinity and s

219 Many popular beliefs and heuristics, such as high tannin wines should be balanced

220 tially faster than general-purpose classical heuristics, such as simulated annealing.

221 orks is computationally infeasible, and thus heuristics, such as the degree distribution, clustering

222 Our method, which combines LSH with several heuristics techniques including soft lowest common ances

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

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

225 behavior that requires higher-order response heuristics that can be applied flexibly over different (

226 nd extracting behavior rely on user adjusted heuristics that can significantly vary across different

227 that the prearcuate gyrus reflects intrinsic heuristics that compute bias signals, as well as the mec

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

229 method can greatly improve upon the speed of heuristics that do not consider the Pareto consensus pro

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

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

232 uctures from objectively random events using heuristics that extend beyond stimulus-outcome condition

233 and seroconversion thresholds, often rely on heuristics that fail to account for individual variabili

234 Specifically, we detail network heuristics that generate structured graphs, such as feed

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

236 ts from the SpliceVarDB, we defined a set of heuristics that inform the evaluation of putative SAVs.

237 Here, we describe a set of data-driven heuristics that inform the interpretation of human splic

238 sis procedure is a series of constraints and heuristics that limit the number of ways metabolites can

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

240 e studies range from experimental probes for heuristics that people employ while thinking ahead to no

241 ary determinant of alignment accuracy, while heuristics that prevent consideration of certain alignme

242 We use a simple set of heuristics that provide a more efficient solution than t

243 tics from keypoint tracking data and creates heuristics that reliably detect behaviors.

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

245 ntegrated within the lattice or conservative heuristics that unduly limit the scope of ligand chemist

246 cisions appears to be the use of simplifying heuristics that works well for the most common condition

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

248 This may be because for successful heuristics the goals of regulators and agents are aligne

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

250 er, there are pitfalls to the use of certain heuristics, the same ones to which humans are prone in e

251 mpetitive behaviour, showing that aggression heuristics, the simple rules that animals use to guide t

252 ial neural networks lack built-in confidence heuristics, they can serve as a test for the necessity o

253 oach to alignment with seeding and expansion heuristics to accelerate discovery of significant alignm

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

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

256 demonstrate this, we present several simple heuristics to allocate control resources across differen

257 show that humans adaptively use compression heuristics to allow larger amounts of social information

258 ce combine fast spatial learning with innate heuristics to choose escape routes with the highest surv

259 build on the theory of ecologically rational heuristics to demonstrate the effect of erroneously plac

260 eady-state mass is a by-product and (ii) use heuristics to design a greedy algorithm.

261 ead, we propose, people use abstractions and heuristics to efficiently identify mutually beneficial a

262 urate RNA pseudoknot searches, we need novel heuristics to ensure that, without degrading the accurac

263 hesis that pre-kindergarten-age children use heuristics to estimate time, and they convert from avail

264 e test a range of scoring metrics and search heuristics to find an effective algorithm configuration

265 Researchers have developed efficient heuristics to identify structural minima on the potentia

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

267 callers rely on hand-engineered features and heuristics to model SVs, which cannot scale to the vast

268 amic incremental search approach among other heuristics to optimize every step of the mapping process

269 mplete representation of a task and then use heuristics to plan future actions in that representation

270 s and (b) inaccurate as they often rely upon heuristics to predict the intensity of each resulting fr

271 optimal local alignment of two profiles with heuristics to preserve continuity within core regions.

272 s constitute computationally cheap but smart heuristics to prevent people from laboring in vain on un

273 CD-Search uses BLAST(R) heuristics to provide a fast, interactive service, and s

274 uences, using local alignment algorithms and heuristics to put together a global spliced alignment.

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

276 hods, with different objective functions and heuristics to search for the optimal MSA.

277 one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed ac

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

279 ch-based approaches that use assumptions and heuristics to speed this up.

280 quantitatively with the goal of developing "heuristics" to define structural requisites governing ac

281 bolic knowledge-based representations (e.g., heuristics) to address effects that motivate QP.

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

283 However, tasks capturing the efficiency of heuristics typically ignore action proficiency in determ

284 ting judgment to such systems may affect the heuristics underlying evaluative processes, suggesting a

285 es (i) relate to the objective functions and heuristics used in MSA methods, and (ii) affect downstre

286 pared to common alternative risk factors, or heuristics, used to inform water lead testing programs a

287 We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel ev

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

289 Cognitive biases and heuristics were found to influence surgical outcomes and

290 e to which people use "irrational" cognitive heuristics when choosing under uncertainty can determine

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

292 Heuristics which implicitly address this problem have em

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

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

295 Wave hybrid solvers that implement classical heuristics with potential assistance from a quantum proc

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

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

298 Moreover, we compared our heuristics with those used in tRNAscan-SE, whose heurist

299 small-brained animals using simple learning heuristics, without the need for a cognitive map.

300 Meanwhile, most useful algorithms are heuristics yielding different near-optimal results upon