ライフサイエンスコーパス: hidden

1 this hierarchy can often be unobservable or 'hidden'.

2 n real-world phenomena might be persistently hidden.

3 5 queries, even when SNPs with MAF <0.05 are hidden.

4 systems biology in elucidating the otherwise hidden actions of microRNAs in PH, as well as areas for

5 ications for uncovering the genetic basis of hidden additive genetic effects and epistatic interactio

6 rdous environments, navigation and detecting hidden adversaries.

7 ined by stress-related factors revealing the hidden aggregation propensity of proteins that otherwise

8 eys performing a task described by different hidden and explicit variables.

9 Essential features of the world are often hidden and must be inferred by constructing internal mod

10 ated observations, but these imputations are hidden and therefore sometimes unrecognized by applied h

11 s for transcription factors (TFs) creating a hidden and unexplored layer of gene regulation.

12 lexities in the membrane associated with the hidden architecture of multiple molecular components, in

13 These findings reveal previously hidden aspects of magnetism in Sm-Co magnets and, by ide

14 e have addressed this problem and found that hidden assay interferences can be unveiled by the graphi

15 d by raw contact frequencies, thus revealing hidden associations between global spatial positioning a

16 ly, with aversive odors triggering otherwise hidden aversions to particular prey colors.

17 sensorimotor conflicts illuminate otherwise-hidden balance impairments, which can be used to increas

18 cquisition of shape and position for objects hidden behind a thick diffuser (~6 transport mean free p

19 existence of a single-chain magnet behavior hidden below the canted antiferromagnetism (T(N) = 5.8 K

20 Answers are hidden beneath their complex and evolving exteriors.

21 fe and death of mummified animals can remain hidden beneath their wrappings.

22 on and interactions in human ARSs, revealing hidden biological functions beyond their catalytic roles

23 analysis, limiting our ability to tease out hidden biological information.

24 ioMethyl, we can successfully identify those hidden biological pathways in DNA methylation data when

25 Finding hidden bodies, believed to have been murdered and buried

26 al approach to determine the presence of the hidden break in 28S rRNAs using mapping of RNA-Seq data.

27 d translation, perturbing the formation of a hidden break in the 23S rRNA and causing abnormal accumu

28 This work reveals a hidden but functional pattern of oxygen octahedral rotat

29 phorylation site on RsbR (T209) is partially hidden by an RsbR flexible loop, whose "open" or "closed

30 tion where the information can be reversibly hidden by applying an electric field and restored by app

31 e two carbasugars reveal mechanistic details hidden by conformational changes that the Michaelis comp

32 outcomes, and (4) reveal indirect feedbacks hidden by current target systems.

33 is and can discover gene expression patterns hidden by noise.

34 ll cycle and environmental responses that is hidden by population-level analysis of gene expression.

35 s filters for uncovering local-scale signals hidden by regional subsidence as detected by interferome

36 cause this single-catalyst-level behavior is hidden by the bulk catalytic behavior.

37 Illustrating imputations hidden by the KM estimator helps to clarify these assump

38 A hidden carbon cycle exists inside Earth.

39 tremendous promise in reproducibly resolving hidden cell populations in complex datasets.

40 This technique allows the decryption of hidden chemical information associated with archaeologic

41 hen be tailored to include relevant abstract hidden cognitive constructs.

42 Our findings reveal a hidden complexity of interactions between a single bacte

43 rotein folding and unfolding and determining hidden conformational changes invisible to other methods

44 ata, including one miscoded variable and one hidden confounder.

45 tion bring to light the dimensionality, as a hidden constraint on carrier dynamics, and identify the

46 -function approach, we discovered previously hidden contributions of YpkA and YopJ to inhibition and

47 artificial selection for yield may entail a hidden cost: the disruption of interactions between plan

48 rea as a radical scavenger, the spin-coupled hidden Cu(II) was observed by EPR spectroscopy.

49 her host-parasite systems to help reveal the hidden death toll of pathogens on wildlife hosts.

50 tal caries, allowing convenient screening of hidden dental lesion sites that are oftentimes omitted b

51 canonical correlation analysis captured two hidden dimensions of brain-behavior relationships: one r

52 onical correlation analysis, for identifying hidden dimensions of cross-modality relationships.

53 tionships in terms of shared miRNAs revealed hidden disease subtyping comparable to that of previous

54 genetic studies have revealed an unforeseen hidden diversity of cryptic species among microscopic ma

55 It has the potential to reveal previously hidden diversity of microscopic life largely due to the

56 we report herein a periodically ordered nick-hidden DNA nanowire (NW) with high serum stability and a

57 e and points to the existence of significant hidden dolomite formation.

58 These costs may remain hidden during the reproductive period of life due to the

59 ions, how rapidly can quantum information be hidden during time evolution?

60 or parameter inference and prediction of the hidden dynamics has been one of the core subjects in sys

61 increasingly being used in science to infer hidden dynamics of natural systems from noisy observatio

62 Similar to how wildfires can reignite from hidden embers not extinguished from an initial round of

63 nts to provide evidence for the existence of hidden entanglement between spin and momentum in the ant

64 ynchronously with the same fabric or with a 'hidden' fabric of 'uncertain roughness'.

65 In this paper, we uncover another hidden facet of the band topology of bismuth by showing

66 er samples were observed over time to reveal hidden factors accounting for the structure of the data.

67 r network characteristics even when they are hidden factors in transcription and mutation profiles.

68 These findings reveal the hidden factors restricting FDHs capability which should

69 ficially selected model organisms can reveal hidden features of the genetic architecture of the compl

70 er, rapid environmental changes can identify hidden fitness trade-offs that turn adaptation into mala

71 We addressed this problem by developing hidden fluid mechanics (HFM), a physics-informed deep-le

72 effects of disturbance on diversity remained hidden for 15 years, at which point diversity began to i

73 tems and that disturbance effects may remain hidden for many years.

74 Here, we reveal a hidden form of inhibitory synaptic plasticity that preve

75 y of non-random vacancy arrangements that is hidden from conventional crystallographic powder analysi

76 ell as in ecological contexts that have been hidden from humans, making the unwatchable seeable.

77 All termini of the components are hidden from nuclease attack, whereas the target-binding

78 eglected because they are "cryptic"-that is, hidden from view (e.g., root production) or difficult to

79 Further, when a moving target is hidden from view by an occluder during a portion of its

80 However, isolated bony elements may reveal hidden functional diversity, providing a more comprehens

81 This approach helps to unveil hitherto hidden functions of some inconspicuous components, which

82 eneration barley pan-genome makes previously hidden genetic variation accessible to genetic studies a

83 We explored the hidden genomic evolution within this genus by performing

84 on (ICMS) encoding egocentric bearing to the hidden goal location.

85 e, we reveal the physics underlying one such hidden growth guidance mechanism through a specific exam

86 cells in a highly dynamic state that exposes hidden HA head domain features.

87 design of next-generation clinical tests for hidden hearing disorders.

88 Hidden hearing loss manifests as speech perception diffi

89 ch in the auditory midbrain of gerbils with "hidden hearing loss" through noise exposure that increas

90 o cause hearing problems in noise, known as "hidden hearing loss," but existing studies are controver

91 use hearing difficulties in noise, known as "hidden hearing loss," but support for this hypothesis is

92 threshold shifts, synaptopathy and permanent hidden hearing loss.

93 yesian inference to discover and exploit the hidden hierarchical structure of the environment.

94 Malnutrition or hidden hunger due to micronutrient deficiencies affects

95 ife, providing critical data about otherwise hidden impacts of human-caused environmental change.

96 atures, and identifies regulatory mechanisms hidden in a crop genome.

97 This killer hidden in a social supergene shows that large nonrecombi

98 analyzer is tested also with real explosives hidden in cargo pallets achieving successful detection o

99 The utilization of the information hidden in isomiRs enables MDEHT to increase the power of

100 st that the Abeta-binding site of TTR may be hidden in its tetrameric form.

101 with desired biological activities that are hidden in microbial genomes.

102 le of how protein-based epigenetic switches, hidden in plain sight, can establish a transgenerational

103 vel formulation to prevent 'forced altruism' hidden in previous static algorithms while allowing for

104 ng faces, objects, and a subthreshold motion hidden in the background.

105 h of previously untapped enzymatic resources hidden in the bee bacteriophage community.

106 ber of disease-associated variants are still hidden in the biomedical literature.

107 ponse revealed underlying processes that are hidden in the conventional electrochemical current measu

108 tools are required to unveil the information hidden in the data.

109 as a phase-conjugate mirror--a fact which is hidden in the extensively studied case of the boundary-d

110 ably broader taxonomic diversity, most of it hidden in the fossil record.

111 mental variables, whose features are usually hidden in the high-dimensional space.

112 of one another, unleashing genetic variance hidden in the linkage disequilibrium that accumulates th

113 are large fluctuations enclosing information hidden in the noise which is beyond the dynamic variatio

114 In nature, such symmetries remain hidden in the space of internal degrees of freedom of su

115 mphasizing the importance of rescuing indels hidden in the unmapped reads in cancer and disease studi

116 ften widely scattered across the internet or hidden in their home institutions, with no systematic wa

117 cule level provides access to this otherwise hidden information.

118 propriate computational methods, information hidden inside the isotope distribution is often omitted

119 will enable scientists to unlock previously hidden insights from acoustic data and offers promise as

120 Such hidden instabilities may be important to other spin-pola

121 ween solvent-accessible protein surfaces and hidden interface regions.

122 hidden jars or to guess the identity of the hidden jar, in order to minimize financial loss from a m

123 reported their probability estimates for the hidden jar.

124 chose whether to draw beads from one of two hidden jars or to guess the identity of the hidden jar,

125 he hypothesis that non trivial, interesting, hidden knowledge can be treated as an anomaly and identi

126 ge proportion of the automatically generated hidden knowledge is valid but generally known, we invest

127 rithm that utilizes global inhibition in the hidden layer and is capable of learning early feature de

128 Here, we uncover a hidden layer of Microprocessor regulation via studies of

129 opmental history of naive T cells creates a 'hidden layer' of diversity that persists into adulthood.

130 ge, multi-patient datasets, SAUCIE's various hidden layers contain denoised and batch-corrected data,

131 ethod relying on feature extraction from the hidden layers of a ConvNet, capable of cellular morpholo

132 Hidden layers of DQN exhibited a striking resemblance to

133 tions (penalties) render features learned in hidden layers of the neural network interpretable.

134 ), which employs a neural network with three hidden layers, trains on datasets with predefined cell t

135 ve spacer between (KY) repeats can mimic the hidden length in the Mfp and act as an effective strateg

136 mprises a dozen glossiphoniid species with a hidden life style inside the mantle cavity of their host

137 mollusks, and deciduous forest), and recover hidden linearity embedded in universal 'scaling laws' of

138 ity declines in undisturbed forest represent hidden losses, possibly driven by climate change, that m

139 ted as an observed version of the unobserved hidden Markov chain that generates one of the two intera

140 behavior is well-described by a Hierarchical Hidden Markov Model (HHMM).

141 We develop a Hidden Markov Model (HMM) framework for estimating the a

142 artment predictions are superior to those of hidden Markov model (HMM) sub-compartment predictions.

143 Nase-seq data and PWMs within a multivariate hidden Markov model (HMM) to detect footprint-like regio

144 We then used a three-state hidden Markov model (HMM) to detect musth behaviour in a

145 to active fishing nets within a multivariate hidden Markov model (HMM) to quantify changes in movemen

146 Apollo (i) models an assembly as a profile hidden Markov model (pHMM), (ii) uses read-to-assembly a

147 CR sequences that is based on a phylogenetic hidden Markov model (phylo-HMM).

148 ngitudinal trajectories were modelled with a Hidden Markov Model across multimorbidity patterns.

149 d metagenome databases through complementary hidden Markov model algorithms.

150 It combines a local Bayesian model and a Hidden Markov Model at the genome-wide level and can wor

151 We demonstrated that clustering using a hidden Markov model can reduce a complex set of physiolo

152 The Hidden Markov Model is useful for modelling transitions

153 First, by fitting a hidden Markov model of EMT with experimental data, we pr

154 ved gene discovery method based on iterative hidden Markov model searching and phylogenetic inference

155 erived from the convolutional neural network-hidden Markov model segmentation agreed with clinical es

156 We also develop a Hidden Markov Model that allows visualization of distinc

157 nt predictions, and furthermore integrated a hidden Markov model to constrain state dynamics based up

158 e repeatability of foraging trips and used a hidden Markov model to identify locations of foraging si

159 We develop a Continuous State Hidden Markov model to identify the timing and type of s

160 Dynamic analysis suggested that the hidden Markov model was stable over short periods of tim

161 The proposed hidden Markov model was trained and applied on a large d

162 Our approach is built on a hidden Markov model where the underlying process is a tw

163 Our approach is based on a hidden Markov model where the underlying process is a Wr

164 tion by Genetic Algorithm (GOOGA), couples a Hidden Markov Model with a Genetic Algorithm to analyze

165 We accounted for their behaviour using a Hidden Markov Model, in which recent observations are in

166 Using the BRAVE approach and hidden Markov model-based clustering, we present 25 synt

167 the localization of repeat boundaries and a hidden Markov model-based repeat counting mechanism.

168 positives than the conventional approach of hidden Markov modeling (HMM) followed by hard thresholdi

169 A data-driven approach based on Hidden Markov modeling allowed us to detect event bounda

170 nctional brain dynamics were disclosed using hidden Markov modeling of power envelope activity.

171 Using Hidden Markov modeling of two acoustic and four movement

172 Hidden Markov models (HMMs) are powerful tools for model

173 used to describe many ecological phenomena, hidden Markov models (HMMs) can facilitate inferences ab

174 We use hidden Markov models (HMMs) fitted in a Bayesian framewo

175 are package designed to fit arbitrary custom Hidden Markov Models (HMMs) with a discrete alphabet of

176 Hidden Markov models (HMMs), especially those with a Poi

177 ur predictions using a set of virus-specific Hidden Markov Models and demonstrated that it improves o

178 Hidden Markov models are used to classify sequences by d

179 This tool combines profile hidden Markov models of each smORF family and deep learn

180 We developed the Continuous-State Hidden Markov Models TF (CSHMM-TF) method which integrat

181 Rs, the first application of self-supervised hidden Markov models to discovering microsatellites.

182 Here, we used hidden Markov models to test how wild dog movements were

183 Hidden Markov models were used to characterize behaviour

184 encing data, and progress to a discussion of Hidden Markov Models, which are of particular value in a

185 l and adaptable bioinformatics tool based on hidden Markov models.

186 response modeling; event segmentation using hidden Markov models; and real-time fMRI.

187 on of reconstructed structures, and discover hidden molecular heterogeneities.

188 s with advanced cancer, while suffering from hidden morbidity and unmet needs.

189 f the faces was significantly altered by the hidden motion signal.

190 ferent physical systems, namely, a partially hidden network and a molecular motor.

191 s of ongoing experience can be inferred from hidden neurocognitive architecture and demonstrate that

192 se, thus highlighting the importance of this hidden niche during natural infections.

193 pply a disjunctive inference to identify the hidden object and use this logical conclusion to assess

194 surface ridges appeared to be caused by the hidden object and which were due to the drapery.

195 nts watch reaching actions directed toward a hidden object whose identity is ambiguous between two al

196 Thus, inhibition of hidden oncogenic signaling pathways in DIPG such as Tbet

197 very, new MCR-based disconnections and often hidden opportunities.

198 many facets of intracellular dynamics remain hidden, or can be measured only indirectly.

199 estions for additional experiments to induce hidden order and/or superconductivity in U compounds wit

200 ification and theoretical understanding of a hidden order are difficult.

201 of orbital degrees of freedom needed for the hidden order in [Formula: see text] to occur, as well as

202 Here, we show that EZH2 harbors a hidden, partially disordered transactivation domain (TAD

203 the potential of a crowdsourcing to uncover hidden patient sub-populations, and to accelerate diseas

204 an conventional methods through detection of hidden patterns within large data sets.

205 We also expose and study a hidden performance bias that effected previous classifie

206 e topological surface state is reached and a hidden phase at the zeroth Landau level is uncovered.

207 The hidden phase boundaries that emerge demarcate vacancy-ne

208 lectron systems are often useful for mapping hidden phases with distinct symmetries.

209 "Hidden phases" are metastable collective states of matte

210 ly from their sexual orientation represent a hidden population and are absent from sexual health camp

211 using materials property charts uncover the hidden potential and advantages of dynamic crystals, whi

212 homology search by developing what we call a hidden Potts model (HPM) that merges a Potts emission pr

213 l differences, thereby revealing an a priori hidden, precise temporal structure of population respons

214 reflector to uncover previously acoustically hidden prey.

215 A hidden profile exists when group members individually ha

216 when information is distributed to create a hidden profile.

217 that inhibit and facilitate the discovery of hidden profiles.

218 of the collective choice research focuses on hidden profiles.

219 This hidden provirus is protected from antiviral drugs until

220 hrough these advances, we resolve previously hidden rapid dynamics, including multiple parallel proce

221 e RBD, furin preactivation of the spike, and hidden RBD in the spike potentially allow SARS-CoV-2 to

222 pired variant of replay in which internal or hidden representations are replayed that are generated b

223 HDACi), which have the potential of exposing hidden reservoirs of HIV-1 to elimination by the immune

224 elationship between visual landmark cues and hidden reward locations.

225 Here, we report a previously hidden role of land use in driving the IAV of S(net) by

226 ents demonstrate accurate reconstructions of hidden rooms up to 3 meters in each dimension despite a

227 lectron microscopy to identify a cryptic, or hidden, Se cycle involving the reoxidation of biogenic v

228 ~6.7% of Tor network users connect to Onion/Hidden Services that are disproportionately used for ill

229 tions, the proportion of often illicit Onion/Hidden Services use is more prevalent (~7.8%) in "free"

230 vices, we compile the Bernstein-Vazirani and Hidden Shift algorithms into our native gates and execut

231 ed to gene expression data extract latent or hidden signals representing technical and biological sou

232 ace for the identification and annotation of hidden sources of variation in scRNA-seq data.

233 timulated Raman spectroscopies to reveal two hidden species of an engineered ancestral GFP-like prote

234 pth-resolved experiments are able to reveal "hidden" spectral features, connected to semiconducting,

235 en cycling between a closed, farnesyl moiety hidden state and an opened, farnesyl moiety exposed stat

236 We show how the hidden state framework can resolve a number of puzzles a

237 guities by formalizing remapping in terms of hidden state inference.

238 Often, the hidden state is the Cartesian product of multiple proces

239 ent, but rather subjective beliefs about the hidden state of the environment.

240 nal inference such as global state decoding, hidden state predictions, one-out conditional distributi

241 Each of the hidden state represents a unique combination of RT profi

242 'Hidden state' exploration motivates agents to sample una

243 a distribution whose parameters depend on a hidden state, and the hidden states evolve along the gen

244 ategy consistent with optimal inference of a hidden state.

245 iguous observations to accurately infer the (hidden) state of the world.

246 rld situations there is a cost both for more hidden states and for more hidden timesteps.

247 "space-time" tradeoff between the number of hidden states and the number of hidden timesteps needed

248 ell-cycle and asexual development, revealing hidden states and transcriptional factors associated wit

249 include complex trait interactions alongside hidden states enhances our understanding of the macroevo

250 parameters depend on a hidden state, and the hidden states evolve along the genome as a Markov chain.

251 lations, estimating the model parameters and hidden states from data, and an optimal control strategy

252 These hidden states have a predictable relationship with P(Doz

253 ion) of the mapping between observations and hidden states in a state-dependent or context-sensitive

254 ein stability and occurrence of pathological hidden states in crystals parallel their solution counte

255 emonstrate that the dynamics of HVC include 'hidden states' that are not reflected in ongoing behavio

256 y but can be maintained in 'activity-silent' hidden states, such as synaptic efficacies endowed with

257 t observations, which inform (task-relevant) hidden states.

258 has been hypothesized that individually-rare hidden structural variants (SVs) could account for a sig

259 complex ciliates and mine these data for the hidden structure, patterns, and motifs that are responsi

260 cientists who generate information about the hidden structures within "big data" assets, and medical

261 n methodologies facilitate the discovery of "hidden" structures within "big healthcare data" to help

262 U.S. medical providers charge incorporate a hidden surcharge to cover their costly administrative bu

263 ic time-reversal invariance is replaced by a hidden symmetry emerging at the self-dual point.

264 Strategies rooted in hidden symmetry recognition, C-H functionalization, and

265 losures which lack any type of (geometric or hidden) symmetry, such as complex networks, buildings, o

266 We conclude that the hidden talents approach is promising, but there is much

267 The hidden talents program sets out to document these abilit

268 research shows that people may also develop 'hidden talents', that is, mental abilities that are enha

269 dren were required to recall the location of hidden targets.

270 This hidden thermodynamic driving motif is ideal for the engi

271 he number of hidden states and the number of hidden timesteps needed to implement any given function.

272 ost both for more hidden states and for more hidden timesteps.

273 nction can be decomposed into a sequence of "hidden" timesteps, demarcated by changes in what state-t

274 he presence of transiently populated states (hidden to conventional crystallographic studies) can be

275 TRAPs, which remain hidden to prior flow diagnostics, thus provide critical

276 y sulfated and complex glycans that remained hidden to the original search.

277 ific information that is often unwritten and hidden to those outside academic social knowledge networ

278 ere, we address this challenge by uncovering hidden TRansient Attracting Profiles (TRAPs) in ocean-su

279 spin, the chain of magnetic atoms unravels a hidden transverse dimensionality that can be exploited t

280 f using chemometrics and sensors to identify hidden trends in environmental parameters, which allow t

281 Relations between task elements often follow hidden underlying structural forms such as periodicities

282 nce of the site-specific uncertainty such as hidden/undetected faults and stress regime.

283 Moreover, each hidden unit has contributions from each of the genes, an

284 alysis of these contributions shows that the hidden units are significantly enriched in known asthma-

285 then used genes that contribute most to the hidden units to develop a secondary random-forest classi

286 Using the trained autoencoder with 50 hidden units, we found that hierarchical clustering on t

287 tial sequestration of Nb relative to Ta in a hidden (unsampled) reservoir.

288 ctures in complex tissues that have remained hidden until now.

289 Therefore, our approach can expose hidden variability in the balance of intrinsic and synap

290 e propose a computational approach to reveal hidden variability in the intrinsic and synaptic conduct

291 This work reveals an important hidden variable that shapes the temporal structure of mo

292 and highlight the contribution of previously hidden variables to the observed population heterogeneit

293 properties of individual molecules which are hidden when measured using ensemble averaging methods.

294 hers develop new methods to unearth patterns hidden within complex data, it is natural to think of th

295 he "phosphatase activation domain (PAD)", is hidden within native Tau in a 'paperclip'-like conformat

296 cells constitute a pretectal cell population hidden within the dorsal thalamus of mammals.

297 arning based method to automatically detect 'hidden' writings and map material variations.

298 riction measurements to isolate a previously hidden yet substantial electronic contribution to the en

299 This implicit model of active gaze may be a hidden, yet fundamental, part of the rich process of soc

300 chers with tremendous opportunity to extract hidden, yet undiscovered, knowledge.