ライフサイエンスコーパス: hide

1 g slower-moving material that was previously hidden.

2 s flawed because only vocal articulators are hidden.

3 threat levels when it pays their enemies to hide?

4 Loss of HID-1 causes a reduction in the number of LDCVs and affe

5 e implicated the peripheral membrane protein HID-1 in neuropeptide sorting and insulin secretion.

6 We propose that HID-1 influences early steps in LDCV formation by contro

7 HID-1 KO cells also exhibit defects in TGN acidification

8 Using CRISPR/Cas9, we generated HID-1 KO rat neuroendocrine cells, and we show that the

9 crine cells, and we show that the absence of HID-1 results in specific defects in peptide hormone and

10 Backmasking is a recording technique used to hide a sound or message in a music track in reverse, mea

11 An ongoing question is, "Where is HIV hiding?" A well-studied HIV reservoir is "resting" T cel

12 honons, while simultaneously suppressing the hidden action of disorder.

13 tice in the food industry, being a potential hidden allergenic commodity.

14 A straightforward approach to identify hidden allosteric sites is demonstrated in protein tyros

15 penetrance of treatment, but a profound yet hidden alteration to the animals' patterning circuitry.

16 ental techniques, that Pd-Ni-P alloys have a hidden amorphous phase in the supercooled liquid region.

17 When the hidden and apparent proteomes are combined, the accuracy

18 ises these data, relevant knowledge is often hidden and hard to identify.

19 carbene carbon atoms by employing the so far hidden and unique ability of the cAACs.

20 Collagen was extracted from raw bovine hide and hydrolyzed by one of three enzymes - Alcalase,

21 An extra dimension of the grating is hidden, and the surface plasmon excitations, though loca

22 For c/a > 0.99, hidden antiferromagnetism was revealed and the magnetisa

23 ase subtilisin enables mapping of previously hidden areas of the proteome.

24 in a position corresponding to one's unseen hidden arm, while increasing their communication with re

25 This lineage had remained hidden as a taxonomic 'blind spot' because of mismatches

26 of progenitor cells can now be used to study hidden aspects of human lung development and pediatric l

27 rea surveillance to reveal patterns that are hidden at the national level, gives communities the hist

28 ch "dark matter" inside cells remains mostly hidden, because our tools were developed to investigate

29 The hide beetle Dermestes maculatus represents an intermedia

30 ected hand feels like one's own hand that is hidden behind the mirror.

31 binding galactose residues that are normally hidden below terminal sialic acid residues.

32 associated with impaired CFR, representing a hidden biological risk, and a phenotype less amenable to

33 By hiding both charged moieties of the zwitterionic compoun

34 Our Structure-seq2 datasets uncover hidden breaks in chloroplast rRNA and identify a previou

35 Both a halogen bond mechanism as well as hidden Bronsted acid catalysis are frequently discussed

36 Our experimental investigations rule out hidden Bronsted acid catalysis by partial decomposition

37 toward a quantum critical point that becomes hidden by a dome of unconventional superconductivity.

38 iscussed liquid-liquid transition previously hidden by crystallization.

39 ntrinsic reaction dynamics that are normally hidden by diffusion.

40 ose phenotypic variation that was previously hidden by functional redundancy among homoeologs.

41 vements in other SLC26 family members may be hidden by inadequate interrogation timescales, and that

42 "Ghost" species hidden by taxa of hybrid origin may be more frequent tha

43 h outcomes with the counterfactual frequency hidden by the disaster itself.

44 e in Pf and Pv transmission that is normally hidden by the high burden of Pv relapses.

45 ce equilibrium isotherms which are typically hidden by the hysteresis effect characteristic of the st

46 more common than generally accepted, albeit hidden by the typical reactivity of organic triflates wh

47 We discovered a previously hidden component of algal and plant nuclear genomes that

48 We subsequently found hidden conformational ensembles within the crystal struc

49 nce, alphaS molecules are forced to access a hidden conformational state on the phospholipid bilayer

50 We employ Markov state models to identify hidden conformations and explore their role in determini

51 current methods by taking into consideration hidden confounders and weak regulations.

52 to relatedness, population structure and/or hidden confounders.

53 ed individuals, population stratification or hidden confounders.

54 However, the presence of complex hidden confounding effects in biological systems can mak

55 udies to determine and explore the nature of hidden confounding variation, most importantly cell comp

56 We also uncover other hidden consequences of employing compartmental models in

57 o undesirable physiological changes, placing hidden constraints on host productivity.

58 summaries, facilitating the exploration of a hidden continuum.

59 ame biological species as well as to confirm hidden cryptic diversity under a single taxonomic name.

60 Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e

61 It unveils previously hidden degradation reactions running in terpenes and nat

62 eep convolutional neural fields to learn the hidden distributions and patterns of boundaries.

63 se instances, the motion microscope uncovers hidden dynamics over a variety of length scales, leading

64 s in flowering phenology, we argue that many hidden dynamics, such as genetic changes, are also takin

65 HIDE-enabled nanoscopy movies span tens of minutes, wher

66 lls which normally express Foxg1 and did not hide endogenous gene tuning.

67 d abstractions that expose key details while hiding enough complexity.

68 tion approach to estimate incidence, and the hidden epidemic (the number of HIV-infected undiagnosed

69 There is a hidden epidemic of cognitive dysfunction in the perioper

70 ease in antigenicity due to exposure of some hidden epitopes.

71 scanning tunnelling microscope tip-assist, a hidden equilibrium phase in a hole-doped bilayer of Sn o

72 n trustworthiness engendered by decisions to hide (experiments 3A and 3B).

73 his novel concept, and we first propose that hidden faces may also be relevant for other specialized

74 lgorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-tru

75 spin-density correlation functions reveals a hidden finite-range antiferromagnetic order, a direct co

76 Our results unveil a hidden footprint of human activities.

77 e, the O:H nonbond dispersion force, and the hidden force to approach equilibrium under compression.

78 identifies symmetry settings with previously hidden forms of band topology, and can be applied to the

79 icing imbalances whose perturbation would be hidden from a conventional gene-centric analysis of gene

80 uasi-enveloped virions in the blood that are hidden from neutralizing antibodies.

81 ignaling in the brain that, although largely hidden from recording methods that observe the spiking a

82 It is, however, hidden from satellite observation, and a lack of globall

83 les (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 3

84 rent postures (participants' body parts were hidden from view).

85 inically manifest have managed to subvert or hide from immunosurveillance.

86 ons in communication, attracting prey and in hiding from predators, particularly for fishes of the de

87 ration, as well as a new discovery route for hidden functions of pathogen genes.

88 Hidden hearing loss (HHL) is a recently described audito

89 This synaptopathy has been termed hidden hearing loss because its effects are not thought

90 threshold elevation, can nonetheless cause "hidden hearing loss" that interferes with coding of supr

91 to permit a simple differential diagnosis of hidden hearing loss.

92 opy can conveniently isolate and detect such hidden high-order photonic excitations.

93 The negative impact of hiding holds whether opting not to disclose unflattering

94 besides other applications, the detection of hidden hydrocarbon reserves, magma build-up before volca

95 and adjacent steric hindrance modulate this hidden hydrophilicity, thus making this scaffold a good

96 The development of hidden image in SPM is achieved by referencing of images

97 Additionally, using a letter as a hidden image, we demonstrated the micro-SORS potential t

98 of cancer development, extremely rare cells hidden in a vast background of regular blood cells.

99 private well water will identify the dangers hidden in America's drinking water supply and redirect a

100 ging brain's ability to hear complex signals hidden in background noise.

101 east 30 distinct patterns of sequence change hidden in mutation databases.

102 nucleation and show that angular momentum is hidden in phantom vortices modes which so far seem to ha

103 sk of missing important microscopic features hidden in the data.

104 ry (142)Nd-depleted reservoir that either is hidden in the deep Earth, or lost to space by impact ero

105 richness of bacterial biosynthetic diversity hidden in the environment, how it varies from one enviro

106 at epitopes of most anti-PrP antibodies were hidden in the folded structure of PrP(RES), even though

107 of the missing heritability of IQ might lie hidden in the human leukocyte antigen (HLA) region, whic

108 surface of the capsid protein VP3, which is hidden in the native virus.

109 underexplored and additional information is hidden in these exceptional collections.

110 terogeneous treatment effects [HTEs]) can be hidden in, and explain discordant results between, treat

111 ce relapse of infection because the bacteria hide in privileged locations.

112 Trypanosome parasites are hiding in human skin, a discovery that may undermine eff

113 e breeding season while reducing the risk of hidden inbreeding due to related founders from the same

114 capability may enable to access the usually hidden information in biochemical reactions like interme

115 of beta which summarize in compact form all "hidden" information specific for the evolving distribute

116 ells (when this corrugation membrane part is hidden inside the pericellular brush layer) and on treat

117 ng likely representative of many similar but hidden interactions sustaining life under highly reducin

118 To uncover hidden interactions, virus mutants that have lost defens

119 These negative judgments emerge when hiding is volitional (experiments 2A and 2B) and are dri

120 While the quantity of hidden knowledge generated by LBD can be vast, we demons

121 t filtering can greatly reduce the number of hidden knowledge pairs generated, (b) for a specific ter

122 esent a detailed analysis of the quantity of hidden knowledge produced by an LBD system and the effec

123 Our world is governed by hidden (latent) causes that we cannot observe, but which

124 standing what additional relationships these hidden layer abstractions have with the cancer cellular

125 color spaces with the fully-connected multi-hidden layer NN.

126 10-layer feed-forward neural network with 1 hidden layer of 10 neurons was trained to predict acuity

127 IC,C), utilizes 11 input variables, a single hidden layer of 4 tanh activation function nodes, and a

128 lends support to our hypothesis that the 1st hidden layer of a deep learning model trained on gene ex

129 We found that addition of a hidden layer of neurons employing non-rewarded STDP crea

130 del selection results indicated that the 1st hidden layer of our deep learning model should contain a

131 Using the 3rd hidden layer representation of each tumor as learned by

132 suggesting that the hidden units in the 3rd hidden layer representations captured a methylation sign

133 erg Marquardt algorithm and 4 neurons in the hidden layer with the correlation coefficient of 0.96 an

134 enes regulated by latent variables at higher hidden layers are often involved in a common biological

135 y, a deep sparse auto-encoder model with two hidden layers, called iSS-PC, was constructed based on m

136 tonians using cold atoms revealed previously hidden local correlations.

137 perianal melanoma is often dismal because of hidden location and diagnosis delay.

138 ortant feature of T2D, and may be driven by 'hidden' LPS.

139 we report on the direct observation of such hidden magnetic correlations via quantum gas microscopy

140 y-product of the meat industry from bone and hide, mainly from bovine and porcine sources.

141 The hidden Markov model (HMM) has been a workhorse of single

142 or that are siblings of the donors, using a hidden Markov model (HMM) of identity-by-descent (IBD) s

143 f highly informative copying states within a Hidden Markov Model (HMM) phasing algorithm.

144 The hidden Markov model (HMM) search tools now use HMMER3, d

145 ently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene predicti

146 omatin-state signatures using a multivariate hidden Markov model (HMM) that explicitly models the com

147 Using a combination of profile Hidden Markov Model (HMM)-based homology searches, netwo

148 a multiple sequence alignment and a profile hidden Markov model (HMM).

149 One such promising method, the infinite hidden Markov model (iHMM), generalizes the HMM that its

150 Here we develop a novel Variational Bayesian Hidden Markov Model (VB-HMM) to investigate dynamic temp

151 We develop an extended hidden Markov model capable of accurately describing the

152 notated existing mitochondrial genomes using hidden Markov model gene profiles.

153 1000 RNA-binding proteins are identified by hidden Markov model searches, of which mRBPs encompass a

154 iological knowledge with the non-homogeneous hidden Markov model that models spatial correlation.

155 eta variables to capture the variances and a Hidden Markov model to characterize the reads dependency

156 ally methylated DNA, we were able to train a hidden Markov model to distinguish 5-mC from unmethylate

157 a software application, AD-LIBS, that uses a hidden Markov model to infer ancestry across hybrid geno

158 orporated the family relationship and used a hidden Markov model to jointly infer CNVs for three samp

159 method represents DNA binding sequences as a hidden Markov model which captures both position specifi

160 Mark (DMR detection based on non-homogeneous hidden Markov model), a novel Bayesian framework for det

161 e this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate c

162 d were as follows: multivariate mixed model, hidden Markov model, logical algorithm, k-nearest neighb

163 we develop a traveling salesman problem and hidden Markov model-based computational method named reC

164 Profile Hidden Markov Model-based homology search has been widel

165 ent library by sampling from an Input-Output Hidden Markov Model.

166 Using Bayesian model selection applied to hidden Markov modeling, we found that SVs oscillated bet

167 is distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequ

168 We used multi-state hidden Markov models (HMM) to characterize states of div

169 This is based on hidden Markov models (HMMs) and is available together wi

170 babilistic models are mostly based on either hidden Markov models (HMMs) or transducer theories, both

171 in families are often represented by profile hidden Markov models (pHMMs).

172 s for understanding time-series data such as hidden Markov models and time-structure based independen

173 sensitive software pipeline based on profile hidden Markov models constructed from manually curated I

174 a robust bioinformatics pipeline exploiting Hidden Markov Models for the identification of nuclease

175 rithm, called Sequence2Vec, which maps these hidden Markov models into a common nonlinear feature spa

176 ost genotype refinement methods are based on hidden Markov models, which are accurate but computation

177 of the more standard classical ones, such as hidden Markov models.

178 in multiple sequence alignment tool based on hidden Markov models.

179 In this paper, we propose a hidden Markov random field (HMRF) based Bayesian method

180 WAS datasets for multiple phenotypes using a hidden Markov random field approach.

181 through Markov state models and the related hidden Markov state models may be used to establish mech

182 Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regio

183 A hidden-Markov model test for selection also found widesp

184 set of high-density, environment-sensitive (HIDE) membrane probes, based on the membrane-permeable s

185 Moreover, hidden memories are remarkably flexible: an instruction

186 mantle may represent one of Earth's largest hidden microbial ecosystems.

187 eflect contextual differences (often termed "hidden moderators") between the original research and th

188 r this activity has features indicative of a hidden movement command.

189 of many disorders, it does not appear to be hiding much of the missing heritability of intelligence.

190 tial of WGS to uncover atypically localized, hidden mutations in patients who lack exonic mutations i

191 eural circuits which has revealed previously hidden neural interactions in a large population of cell

192 al neural networks with a variable number of hidden neurons.

193 hree-dimensional depth imaging, and tracking hidden objects around a corner.

194 e describe a thermoelectric cloak capable of hiding objects from thermoelectric flow.

195 game in which players have to find a target hidden on a board, to investigate how the rounds are inf

196 uld be implicated, and in 1 patient may have hidden or triggered chronic GVHD.

197 This approach provides us with a pathway to "hide" or "reveal" a given ferromagnetic region at zero m

198 nd temperatures, are performed to reveal the hidden order associated with the seemingly-irregular int

199 This behavior reveals that hidden order depends strongly on tuning outside of the U

200 the magnetic proximity coupling stabilizes a hidden order in FeSCs, which may also apply to other str

201 We find that while hidden order is monotonically suppressed and destroyed f

202 The second-order phase transition into a hidden order phase in URu2Si2 goes along with an order p

203 r parameters can be employed to reveal their hidden order.

204 volution of the critical fields for both the hidden-order (HO) and large-moment antiferromagnetic (LM

205 ous values of Fe concentration x in both the hidden-order (HO) and large-moment antiferromagnetic (LM

206 on intermetallic compound URu2Si2 exhibits a hidden-order phase below the temperature of 17.5 K, whic

207 Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of th

208 Hidden orthologs do not show unusual sequence compositio

209 a correlation between the number of putative hidden orthologs in a lineage and its "average" evolutio

210 evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by tr

211 e gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology

212 9 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and H

213 d weak positive selection appear to underlie hidden orthology in Platyhelminthes.

214 analysis of arterial waveform that extracts hidden oscillations in the waveform that we called intri

215 This supra-tauc window was previously hidden, owing to a lack of experimental methods.

216 l, and the scope of the epidemic was largely hidden, owing to generally mild infections and no establ

217 ng itself but also the identification of the hidden paint layers what makes it much more versatile as

218 ltural Heritage that deal, for example, with hidden paintings vandalized with graffiti or covered by

219 Here we uncover the hidden part of the blood proteome via novel SpotLight ap

220 tivity, without the need for pre-existing or hidden pathology.

221 We identified hidden patterns embedded in this time-series gene expres

222 hod offers an alternative way for uncovering hidden patterns embedded in time series gene expression

223 Softness is designed to capture the hidden patterns in relative particle positions that corr

224 h approximates the joint distribution of the hidden peak status by a set of independent random variab

225 The ability to predict hidden phases under extreme conditions is not only cruci

226 h complex network analysis allows to uncover hidden plants relationships related to their evolutionar

227 se, but these estimates might be inflated by hidden pleiotropy.

228 owever, the biological significance of these hidden polypeptides is still unclear.

229 enome-wide association studies (GWAS), where hidden population structure can create fictitious associ

230 ate the sizes of epidemiologically important hidden populations, such as sex workers and people who i

231 ion with submicron precision and reveals the hidden potential for chemotaxis within bacterial biofilm

232 while learning about slot machines yielding hidden preferred and non-preferred food outcomes with va

233 lms grown on (001) substrates, and observe a hidden, previously unreported, non-equilibrium structure

234 Computational modeling can reveal hidden principles of the system by classification of ind

235 n within the plasma membrane to generate the HIDE probe DiI-SiR.

236 HIDE probes also facilitate acquisition of live-cell, tw

237 HIDE probes such as DiI-SiR are non-toxic and do not req

238 challenges, which are mainly related to the hidden programming languages and electronic details of t

239 Interactions can reveal otherwise hidden properties of intentional agents, such as thought

240 While it is applied to estimate the hidden properties of the thalamus and explore the mechan

241 -time capability to estimate thalamocortical hidden properties with high precision under both normal

242 l-time estimation system for thalamocortical hidden properties.

243 with Lewy Bodies (DLB), on peptide level the hidden proteome contributed almost as much information t

244 together, these results reveal a previously hidden relationship between cellular metabolism and geno

245 complex traits in founder populations, where hidden relationships may augment the inherent genetic in

246 f storing the entire mass of the oceans as a hidden reservoir.

247 t just of the risk of revealing, but of what hiding reveals.

248 We previously identified a class of hidden self-antigens known as T cell epitopes associated

249 cruited in a similar manner by conserved but hidden sequence patterns in the M protein.

250 monic nanoparticle substrates, revealing the hidden shape of the nanoparticles while also mapping loc

251 nal framework which effectively utilizes the hidden shared knowledge from some MMP types to enhance p

252 topher Goatley and Simon Bran introduce the 'hidden' small fishes found on coral reefs.

253 ate gradient of temperature can highlight or hide some sensorial attributes.

254 ifferent assemblies will represent different hidden sources of upstream firing activity.

255 We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction s

256 muli provide ambiguous information about the hidden state of the environment, leading to the proposal

257 xual systems influence diversification using hidden state speciation and extinction analysis (HiSSE).

258 ording to the dynamic coding framework, such hidden state transitions flexibly configure memory netwo

259 nattended items remain robustly coded in the hidden state, decoupling attentional focus from cue-dire

260 ent to wipe the corresponding trace from the hidden state.

261 Finally, the strength of hidden-state coding predicts the accuracy of working-mem

262 arning rule that combines cached values with hidden-state inference.

263 signal based on an inferred distribution of hidden states (a 'belief state').

264 a perturbation approach to measure mnemonic hidden states in an electroencephalogram.

265 ional system guides inference concerning the hidden states of other agents, such as their beliefs, pr

266 vides optimal online estimates of unknown or hidden states of the world, based on previous observatio

267 PSSV features a mixture model with hidden states representing different mutation patterns;

268 To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprint

269 s a TD learning framework that operates over hidden states.

270 ramework can automatically extract effective hidden structural features from the encoded raw sequence

271 This representation reveals hidden structure-function relationships in biomolecules.

272 x 10(-4) in an ANCOVA with an adjustment for hidden substructures).

273 eveals the O'Nan pariah group as a source of hidden symmetry in quadratic forms and elliptic curves.

274 of the depleted isotopes is useful to limit hidden systematic errors.

275 an participants make reaching movements to a hidden target and receive positive reinforcement when su

276 In hidden-target learning and probe trials, hAPP mice and M

277 ed for compound screening measurements like "hidden-target screening" in complex environmental matric

278 telomeres into the t-loop structure, thereby hiding telomere ends from double-stranded break repair a

279 paradigm to investigate the neural basis of "hidden", temporarily active representations in the servi

280 ose differently, so that they benefited from hiding their actions.

281 auses of phenotypic variation that have been hidden to date.

282 variations occurring within a few years are hidden to routine measurement techniques.

283 rs when animals consume plants; but the term hides two fundamentally different processes.

284 with common clinical manifestations that are hidden under the current periodontal classification sche

285 eving dynamic features that may otherwise be hidden under the linear spectrum; its extension to the t

286 ith favorable prognosis, suggesting that the hidden units in the 3rd hidden layer representations cap

287 rning algorithms that use multiple layers of hidden units to capture hierarchically related, alternat

288 eep learning model should contain about 1300 hidden units to most effectively capture the covariance

289 xtensive genetic variation that has remained hidden until now.

290 yer of observed variables and four layers of hidden variables.

291 in which differential states are embedded as hidden variables.

292 which can be combined to uncover previously hidden variation.

293 ge property enhancements may however also be hidden within already well-known materials, when their s

294 shed light on this question by showing that, hidden within the antigenic variability of many M protei

295 data to identify large-scale unknown effects hidden within the data.

296 ng intergenic/intervening ncRNAs (lincRNAs), hidden within the large amount of information obtained t

297 mall, flightless and anachoretic insect that hides within its host's sleeping area manages to travel

298 Detecting and healing these hidden wounds may help prevent and treat psychopathology

299 In turn, these "hidden wounds" of childhood trauma can affect brain deve

300 e micro-SORS potential to reconstruct also a hidden writing covered, for example, with paper sheets t