ライフサイエンスコーパス: probabilistic

1 We created a probabilistic algorithm to identify new and existing SNA

2 Deterministic and probabilistic analyses were undertaken to examine the ef

3 igh throughput predictions and propose a new probabilistic analysis of rules for glass forming abilit

4 Altogether, we envision that probabilistic analysis of single-cell phenotypes complem

5 In probabilistic analysis, at a willingness to pay of $5000

6 rot 2.0 include the characterization of both probabilistic and deterministic entanglements which can

7 Probabilistic and deterministic sensitivity analyses wer

8 sence, quality, or similarity of objects are probabilistic and inform behavioral decisions that are o

9 The conclusion remains robust in probabilistic and one-way sensitivity analyses.

10 eview the fundamentals of the most impactful probabilistic and signal processing algorithms.

11 rching theoretical framework, by integrating probabilistic and structural approaches, to establish nu

12 Cl), we find that plectoneme pinning becomes probabilistic and the pinning probability increases with

13 sion (SPDC), a process that is intrinsically probabilistic and thus relegated to a regime of low rate

14 First, we use a probabilistic approach based on the maximum information

15 osed method was studied using 54 drugs and a probabilistic approach of performance evaluation using b

16 To tackle this limitation, we propose a probabilistic approach rooted on the statistical concept

17 tained heavy metals was assessed by means of probabilistic approach.

18 environments, we induce context-task demand probabilistic associations and find that learned associa

19 tability or readiness.SIGNIFICANCE STATEMENT Probabilistic associations between stimuli afford memory

20 Probabilistic associations between stimuli afford memory

21 Participants performed a probabilistic associative learning task, and we employed

22 Instead they use simple probabilistic assumptions to model such uncertainties.

23 e corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fract

24 evaluated using five different classifiers: probabilistic bayesian, Support Vector Machines (SVM), d

25 dings reveal that the saccadic system uses a probabilistic-Bayesian control strategy to compensate fo

26 The model predicts sensory activity and probabilistic behavior during animal navigation in diffe

27 ividual herpesvirus virion particles enables probabilistic bet hedging between viral replication and

28 ment packaging provides a mechanism enabling probabilistic bet hedging between viral replication and

29 Probabilistic bet hedging, a strategy to maximize fitnes

30 Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete te

31 The model is represented as a probabilistic bipartite graph, which can handle highly c

32 better than the null models with respect to probabilistic calibration, and that this would have been

33 nse-contingent reward processing in a visual probabilistic categorization task.

34 tome profiling and applied network-based and probabilistic causal methods to identify severe asthma g

35 By applying probabilistic causal methods to these gene signatures an

36 These probabilistic causal models enabled detection, prioritiz

37 Here we introduce probabilistic cell typing by in situ sequencing (pciSeq)

38 returns from first migration correlate with probabilistic changes in latitude at recruitment, in doi

39 Using the Wasserstein distance to measure probabilistic changes, we discovered that brain regions

40 sures of ESM skill can help produce reliable probabilistic characterization of climate extremes.

41 Monkeys performed in a probabilistic choice task in which the statistical varia

42 same ESS prior to HIREC (fixed polymorphism, probabilistic choice, or cue dependency), can have a sub

43 EMENT Our lives are peppered with uncertain, probabilistic choices.

44 ing human visual learning results requires a probabilistic chunk-learning model, whereas a simple fra

45 We present Epiclomal, a probabilistic clustering method arising from a hierarchi

46 ile molecular noise in its expression adds a probabilistic component to the model.

47 Bayesian optimality, while still performing "probabilistic computation" in the sense that they take i

48 nhanced safety learning, as measured using a probabilistic computational model, while trait cognitive

49 transistors (FETs), as a class of analog and probabilistic computational primitives for hardware impl

50 learning models and neural theories consider probabilistic computations as an efficient way to solve

51 Execution of probabilistic computing algorithms require electrically

52 Probabilistic computing(1,5-7) is another unconventional

53 rating correlations or anti-correlations for probabilistic computing.

54 explicit probability estimates in different probabilistic contexts (easy vs. difficult conditions) a

55 The majority of the probabilistic cost-effectiveness model iterations favore

56 address these challenges, we have designed a probabilistic data structure called a multiindex Bloom F

57 sted the hypothesis that difficulty adapting probabilistic decision-making to second-order uncertaint

58 two experiments, we modeled performance on a probabilistic decision-making under volatility task usin

59 ate decodable outcome representations during probabilistic decision-making, which are sequentially st

60 n which progenitor cells undergo a series of probabilistic decisions that lead to the specification o

61 It should be based on a probabilistic definition of a cell type and incorporate

62 BART provided a reliable probabilistic description of the likelihood of interacti

63 study tested performance of an AI system for probabilistic diagnosis in patients with 19 common and r

64 ainable intermediate imaging features, and a probabilistic differential diagnosis that performed at t

65 rough a data-driven modelling approach using probabilistic dimensionality reduction, we investigate c

66 likely leads to the impaired performance in probabilistic discounting following acute toluene exposu

67 veillance, we constructed accuracy-weighted, probabilistic ensemble models from these base models.

68 tactile learning.SIGNIFICANCE STATEMENT In a probabilistic environment, the prior belief of sensory e

69 EPISCORE applies a probabilistic epigenetic model of gene regulation to a s

70 al variables analysis and takes advantage of probabilistic eQTL annotations to delineate and tackle t

71 We present a robust probabilistic estimate of average GLOFs return periods i

72 mation?(1) Here we show that curiosity about probabilistic events depends on multiple aspects of the

73 t function as a reduction in entropy under a probabilistic evolutionary model fitted to human and non

74 Reaction times were modulated by probabilistic expectations based on cue reliability and

75 amplitude reflects primarily breaches of non-probabilistic expectations, rather than target probabili

76 IPER (Subcompartment iNference using Imputed Probabilistic ExpRessions), based on denoising autoencod

77 The proposed P-values and PIPs lead to probabilistic feature selection of single cells that can

78 Lastly, it uses a battery of probabilistic folding algorithms that incorporate all po

79 This study proposes a method for probabilistic forecasting of the disease incidences in e

80 a combination of tailored deterministic and probabilistic forecasts can inform key prevention and co

81 Probabilistic forecasts for the occurrence of El Nino/La

82 With the categorical probabilistic forecasts of disease incidences, this earl

83 The 2015-2016 challenge consisted of weekly probabilistic forecasts of multiple targets, including f

84 whole genome sequencing data and proposes a probabilistic formulation for estimating variant allele

85 c gene clusters, we developed METACLUSTER, a probabilistic framework for characterizing metabolic gen

86 The probabilistic framework has direct application to conser

87 e simulation results in relation to a simple probabilistic framework that captures the power law depe

88 Here, we introduce HapTree-X, a probabilistic framework that utilizes latent long-range

89 Here we present a probabilistic framework to reconstruct sea level since 1

90 ey combine predictable toe pad friction with probabilistic friction from their claws, which they drag

91 Our software implements a probabilistic, fully Bayesian model of screen data.

92 PerturbNet uses a probabilistic graphical model to directly model the casc

93 l framework that combines the formulation of probabilistic graphical modeling, standard statistical e

94 ased on regularized multivariate regression, probabilistic graphical models and artificial neural net

95 show that due to their probabilistic nature, probabilistic graphlet-based methods more robustly captu

96 We introduce probabilistic graphlets as a tool for analyzing the loca

97 obability distributions and demonstrate that probabilistic graphlets outperform their unweighted coun

98 surprisingly, the syntactic rules underlying probabilistic grooming transitions possess action durati

99 The main interest of probabilistic GTM maps is to attain two objectives with

100 nsively evaluated this method, called PRIME (PRobabilistic IMputation to reduce dropout effects in Ex

101 the same features as continuous measures in probabilistic "individualized prediction" models.

102 Although this suggests a possible role for probabilistic inference and expectation in adaptive beha

103 This allows us to perform probabilistic inference of admixture proportions of ance

104 range, reducing redundancy, and facilitating probabilistic inference.

105 rtical hypercolumn to perform sampling-based probabilistic inference.

106 points to a more instantaneous evaluation of probabilistic information.

107 heories that cast perception as a process of probabilistic integration of prior knowledge and sensory

108 ationally; and (iii) epigenetic elements are probabilistic, interactive regulatory factors and not de

109 adox we propose a two-process model in which probabilistic knowledge initially biases perception towa

110 Probabilistic latent semantic analysis (pLSA) is commonl

111 , 13 female) reached learning criterion in a probabilistic learning task with a reversal component.

112 In a probabilistic learning task, participants predicted the

113 nger adults (male and female) performing two probabilistic learning tasks with varying attention dema

114 n choice data in two independent datasets of probabilistic learning tasks.

115 A probabilistic limit on the number of items successfully

116 efficient integer linear programming, (ii) a probabilistic logic implementation for semi-quantitative

117 with contact data and genetic sequence in a probabilistic manner for the first time.

118 Here, we present probabilistic mapping data on a large cohort of patients

119 The probabilistic mapping method using Benjamini-Hochberg ge

120 Probabilistic maps assessed CBH location and likelihood

121 nuclei densities were determined by applying probabilistic maps to MPRAGE T1 sequences processed usin

122 Here, I propose probabilistic measures of split similarity, which allow

123 We analyzed feature uncertainty using two probabilistic measures, and found that feature uncertain

124 ogether, these observations suggest a novel, probabilistic mechanism by which Abl biases the stochast

125 al studies indicate that ClpXP operates by a probabilistic mechanism in which five to eight residues

126 logical substrates of anticipation following probabilistic memory cues that carry spatial or temporal

127 Here, we present a probabilistic Mendelian randomization (MR) method, PMR-E

128 Here, we describe a novel probabilistic method called IBDmix to identify introgres

129 We utilized mutational mapping, a powerful probabilistic method for studying sequence evolution, to

130 We propose a principled probabilistic method that does not assume any a priori c

131 ions at the pathway level, wherein it uses a probabilistic method to characterize the likelihood of m

132 ethod to measure their transcriptomes, and a probabilistic method to interpret these measurements.

133 We propose a novel probabilistic method to quantitatively assess these risk

134 Here, we introduce ROHan, a probabilistic method which substantially improves the es

135 We describe a probabilistic method, DuploMap, designed to improve the

136 To address this challenge, we propose a probabilistic method, inspired by percolation theory, to

137 sets, we show that Epiclomal outperforms non-probabilistic methods and can handle the inherent missin

138 ida Current transport during 1909-2018 using probabilistic methods and principles of ocean physics ap

139 dress limitations of IgScout by developing a probabilistic MINING-D algorithm for D gene reconstructi

140 Here we develop a Bayesian probabilistic model for CFC-11, 12, and 113 banks and th

141 This is achieved by first developing a probabilistic model for the prevalence of vp1 sequences

142 Our character-level language model learns a probabilistic model of 1-dimensional stochastic trajecto

143 g reward contingencies, we derived a unified probabilistic model of CA1 representations centered on a

144 ngle-cell data, we developed a quantitative, probabilistic model of cone cell decisions in the retina

145 ructured internal dynamics in a hierarchical probabilistic model of natural images.

146 Using a probabilistic model of transgenerational TL and populati

147 We develop a probabilistic model of transport and mixing of tracer pa

148 of the underlying variability, an objective probabilistic model that accounted for all of the data i

149 indings suggest the existence of an internal probabilistic model that facilitates behavioral adaptati

150 e incorporate distinguishing features into a probabilistic model that infers the number of cells to s

151 We developed Watershed, a probabilistic model that integrates multiple genomic and

152 rcome these issues, we present CellAssign, a probabilistic model that leverages prior knowledge of ce

153 work to add context for homology transfer, a probabilistic model to account for the uncertainty in la

154 A "bottom-up" probabilistic model was developed using engineering firs

155 In this study, we propose a novel probabilistic model, CoMM-S2, to examine the mechanistic

156 In addition, as a probabilistic model-based approach, BREM-SC is able to q

157 s different tissues explicitly via a unified probabilistic model.

158 Models TF (CSHMM-TF) method which integrates probabilistic modeling of scRNA-Seq data with the abilit

159 a distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific asp

160 , a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic bio

161 hromosomal conformation capture coupled with probabilistic modelling of experimental noise to resolve

162 based on importance sampling, using simpler probabilistic models as proposal distributions.

163 Over time, several probabilistic models have been proposed that account for

164 To test our second hypothesis, we used probabilistic models of expected species co-occurrence p

165 ies suggest that organisms learn and exploit probabilistic models of their environment.

166 Probabilistic models provide a low-error, compressed rep

167 Probabilistic models such as Bliss independence have bee

168 ergistic efficacy in drug combinations using probabilistic models such as Bliss independence.

169 We then construct probabilistic models-specifically, marked renewal proces

170 subpopulations by constructing and comparing probabilistic models.

171 Third, their probabilistic nature allows them to be used directly in

172 luation phase and (ii) the deterministic vs. probabilistic nature of initial reinforcement.

173 Third, the probabilistic nature of the transmission was noted, as i

174 We show that due to their probabilistic nature, probabilistic graphlet-based metho

175 rks can then be efficiently aligned by using probabilistic network alignment techniques, thereby yiel

176 l for analyzing the local wiring patterns of probabilistic networks.

177 Through Probabilistic Neural Network (PNN) analysis, 85.3% were

178 EG field patterns during presentation of two probabilistic outcomes (reward, loss), and then apply th

179 in (CTMC) model is formulated to investigate probabilistic outcomes of coinfections.

180 s is also the case when integrating multiple probabilistic outcomes of the same action.

181 tochastic interaction or correlation between probabilistic (p-) bits.

182 in phenotype prediction problems, since the probabilistic parameterization of the uncertainty space

183 Probabilistic, particle-based nonlocal models may addres

184 (OFC), while freely moving rats performed a probabilistic Pavlovian learning task.

185 Probabilistic phenotype metrics offer the following thre

186 Statistical learning and probabilistic prediction are fundamental processes in au

187 t has been proposed that people can generate probabilistic predictions at multiple levels of represen

188 ed gating tasks to generate estimates of the probabilistic predictions generated by these constraints

189 ilt in the next engineering cycle, alongside probabilistic predictions of their production levels.

190 We designed a probabilistic predictive model and trained it using Baye

191 Consistent with probabilistic predictive processing accounts, we found e

192 reduction of the inflammatory markers using probabilistic principal component analysis, we observed

193 nderstand causal relationships in real-world probabilistic problems such as diagnosis, forecasting, c

194 The initiation of an intestinal tumour is a probabilistic process that depends on the competition be

195 We develop a probabilistic, process-based valuation of the effects of

196 gence strategy, comprising deep learning and probabilistic programing of RNA-seq data, causally linke

197 Probabilistic programming is a powerful methodology for

198 e for the model has been developed using the probabilistic programming language Stan.

199 ing Pathway Sampling, in Julia using the Gen probabilistic programming language.

200 r results demonstrate the vast potential for probabilistic programming, and Gen specifically, for bio

201 Observed climate data and spatially coherent probabilistic projections of daily future weather were d

202 nfluence the resistance of reward seeking to probabilistic punishment and to identify the mPFC as a r

203 ding of risky actions by mPFC is involved in probabilistic punishment learning and provide a novel be

204 n particular, females were more sensitive to probabilistic punishment than males.

205 that this region is involved in learning of probabilistic punishment.

206 dy from Skane, to derive bias parameters for probabilistic quantification of bias, to correct the haz

207 ification and unmeasured confounding through probabilistic quantification of bias.

208 uple process-based models and data, yielding probabilistic quantification of model parameters, system

209 the single-cell data allow us to obtain the probabilistic rates of promoter switching, transcription

210 dversity, indicating that these pathways are probabilistic, rather than deterministic, and prolonged

211 g our model, we produce an observation-based probabilistic reanalysis of surge extremes covering the

212 All experiments employed two versions of a probabilistic reasoning (beads) task, which required par

213 Impaired probabilistic reasoning and the jumping-to-conclusions r

214 with SCZ-a state associated with compromised probabilistic reasoning due to reduced glutamatergic neu

215 butes to jumping to conclusions and impaired probabilistic reasoning in SCZ.

216 paired information sampling and to disrupted probabilistic reasoning, namely to overweighting of sens

217 soning and cannot be explained by anchoring, probabilistic reasoning, or generic perspective taking.

218 We also estimated probabilistic relationships between stillbirth rates and

219 lore controls on belowground carbon cycling: Probabilistic Representation of Organic Matter Interacti

220 Staged partial and probabilistic restraint allows mice to adjust to self-in

221 d decision making in adult male rats using a probabilistic reversal learning task and used positron e

222 approach and examined flexible behavior on a probabilistic reversal learning task in 572 children, ad

223 but not of saline, disrupted behavior in the probabilistic reversal learning task measured by selecti

224 ally in reward-guided choice behavior on the probabilistic reversal learning task predicted greater e

225 mGluR5) and assessed decision making using a probabilistic reversal learning task.

226 n subjects (female: 21, male: 6) performed a probabilistic reversal learning task.

227 sed sample of subjects who participated in a probabilistic reward learning task during event-related

228 t that repeated engagement with heavily cued probabilistic reward schedules can drive addiction vulne

229 dition, a subgroup of patients tested with a probabilistic reward task (n = 9) showed increased rewar

230 e of effort-related decision-making, and the Probabilistic Reward Task (PRT) measure of reward learni

231 ral striatum), better reward learning in the Probabilistic Reward Task (PRT), and lower anhedonic sym

232 The probabilistic reward task and resting-state functional m

233 d learning was measured using a computerized probabilistic reward task.

234 re published in peer-reviewed journals; used probabilistic sampling methods and systematic PTSD asses

235 ptide-pair encoding (PPE), a general-purpose probabilistic segmentation of protein sequences into com

236 me measures based on participant report, non-probabilistic selection of community-level workers' catc

237 enance, and training, and did univariate and probabilistic sensitivity analyses for UAS lifespans, ra

238 We used probabilistic sensitivity analyses to account for parame

239 We conducted deterministic and probabilistic sensitivity analyses to examine the impact

240 We performed stochastic and probabilistic sensitivity analyses to identify parameter

241 Deterministic and probabilistic sensitivity analyses using appropriate par

242 Probabilistic sensitivity analyses were below per capita

243 Univariable and probabilistic sensitivity analyses were conducted to eva

244 One-way and probabilistic sensitivity analyses were performed to tes

245 One-way, two-way, and probabilistic sensitivity analyses were performed.

246 health system objective) and did one-way and probabilistic sensitivity analyses with determination of

247 In probabilistic sensitivity analyses, GT and DOT were pref

248 In probabilistic sensitivity analyses, RZV remained the pre

249 el parameters were used in deterministic and probabilistic sensitivity analyses.

250 and effects and performed 1-way, 2-way, and probabilistic sensitivity analyses.

251 arameter uncertainty using deterministic and probabilistic sensitivity analyses.

252 puts was assessed by using deterministic and probabilistic sensitivity analyses.

253 h uncertainty incorporated in both 1-way and probabilistic sensitivity analyses.

254 s was addressed in univariable, scenario and probabilistic sensitivity analyses.

255 ost per DALY averted and death averted, with probabilistic sensitivity analyses.

256 reening ANalysis model was used to conduct a probabilistic sensitivity analysis (PSA), consisting of

257 to-pay threshold in 74% of iterations in the probabilistic sensitivity analysis and was most sensitiv

258 A probabilistic sensitivity analysis assessed uncertaintie

259 Probabilistic sensitivity analysis confirmed that transi

260 Probabilistic sensitivity analysis favored no teduglutid

261 Probabilistic sensitivity analysis favored transplantati

262 o activity was most cost-effective in 64% of probabilistic sensitivity analysis iterations.

263 In probabilistic sensitivity analysis, screening at ages 10

264 In probabilistic sensitivity analysis, the probability that

265 with 95% uncertainty intervals (UIs) from a probabilistic sensitivity analysis.

266 The conclusion was robust in a probabilistic sensitivity analysis.

267 ntitatively predicts human reaction times in probabilistic sequential motor tasks.

268 tafamidis was cost-effective in 0% of 10 000 probabilistic simulations.

269 cell RNA-seq datasets, and model them with a probabilistic simulator.

270 hortages on Britain's power supplies using a probabilistic spatial risk model of regional climate, hy

271 (n=63 patients) were coregistered to create probabilistic stimulation atlases.

272 Furthermore, we aimed to construct a probabilistic stimulation map of effective DBS.

273 We applied probabilistic stimulation mapping to a retrospective, mu

274 ance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated ar

275 Probabilistic stimulation maps and non-parametric permut

276 Prior knowledge about the probabilistic structure of visual environments is necess

277 Here, we define HWEs and analyze their probabilistic structure using time series of still-water

278 mmonly used signal processing methods, and a Probabilistic Symbolic Pattern Recognition (PSPR) method

279 mediating the precision of prediction during probabilistic tactile learning.SIGNIFICANCE STATEMENT In

280 nvironment may be needed to improve auditory probabilistic thinking.

281 and healthy control participants completed a probabilistic three-choice decision-making task.

282 tional feedback loops by the introduction of probabilistic time-delays.

283 We developed a probabilistic time-in-state cohort model that compared a

284 network, then tracked between frames using a probabilistic tracking algorithm to approximate movement

285 estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of

286 ticocortical connections was estimated using probabilistic tractography analyses.

287 d network properties using graph theory from probabilistic tractography and calculated changes in psy

288 The CB was tracked using probabilistic tractography and split into anterior and p

289 Probabilistic tractography indicated that 10%-20% of int

290 k connectivity of these regions, we employed probabilistic tractography on diffusion tensor imaging d

291 We applied probabilistic tractography to diffusion-weighted images,

292 dial thalamus (n = 32) were used to generate probabilistic tractography to form a normative structura

293 inhibition networks were reconstructed with probabilistic tractography using the participant-specifi

294 networks were reconstructed with seed-based probabilistic tractography.

295 We propose a new computational framework, probabilistic transcriptome-wide association study (PTWA

296 To address this gap, we developed a probabilistic transmission model of HPAIV H5N1 in the no

297 utocorrelation on epidermis), that describes probabilistic two-dimensional stomatal distributions bas

298 indirectly through other species, including probabilistic uncertainty in parameters, model specifica

299 ally, these models are defined in terms of a probabilistic V(D)J recombination model which is sometim

300 original qualitative data into a continuous, probabilistic variable better suited to quantitative ana