ライフサイエンスコーパス: for inferring

1 V1 and RL.SIGNIFICANCE STATEMENT A major cue for inferring 3D depth is disparity between the two eyes

2 sampling of the parameter space is critical for inferring a correct model structure.

3 llenges, we present a novel algorithm DLCpar for inferring a most parsimonious (MP) history of a gene

4 diversity, but this is nonetheless essential for inferring accurately the history of species with ove

5 ms originate from the motor system and allow for inferring actions from environmental affordances, an

6 Many approaches for inferring adaptive molecular evolution analyze the u

7 ion concern, and provide a general framework for inferring allele distribution and persistence and in

8 ve methods for estimating site allele count, for inferring allele frequency spectrum and for associat

9 The rate limiting factor for inferring an association between a variant and a phe

10 We present an algorithm for inferring ancestry segments and characterizing admix

11 results and developing computational methods for inferring and analyzing these networks.

12 ple algorithms provide a stronger foundation for inferring and characterizing regulatory programs ass

13 We present a method for inferring and constructing transport reactions for t

14 le feedback pathways that provide mechanisms for inferring and interpreting what sensory inputs are a

15 (2020) present an algorithm for inferring and inverting such trial-to-trial differen

16 and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of

17 Mitochondrial genomes have been useful for inferring animal phylogeny across a wide range of cl

18 This resource will be useful for inferring bacterial gene function and provides a dra

19 We apply the joint modeling approach for inferring base pairing states on simulated data sets

20 These findings establish Collage as a method for inferring biological knowledge from the integration

21 Sparse Gaussian graphical models are popular for inferring biological networks, such as gene regulato

22 ck size estimates, we introduce a new method for inferring bottleneck sizes that accounts for these f

23 Here we present a framework for inferring cancer-related gene overexpression resulti

24 P method quantifies confidence probabilities for inferring causal structures and thus leads to more r

25 lities, ScisTree implements a fast heuristic for inferring cell lineage tree and calling the genotype

26 ontent of our repository, provide procedures for inferring cell-cell communication networks from sing

27 r of estimated cell types are critical steps for inferring cell-type proportions.

28 We developed a tool for inferring cellular architectures across many domains

29 ining, making V. monoica a suitable outgroup for inferring changes in papaya sex chromosomes.

30 a method, similar to regression calibration, for inferring changes in the distribution of white blood

31 od based on water mass transformation theory for inferring changes in the water cycle from changes in

32 Here, we present a new method, CloneSeeker, for inferring clinical heterogeneity from sequencing dat

33 seq) technologies produce data that is ideal for inferring CNAs.

34 integer copy number, few have been designed for inferring CNV haplotypic phase and none of these are

35 es, predicting CNV allelic configuration and for inferring CNV haplotypic phase from SNP/CNV genotype

36 of genome-scale data can serve as the basis for inferring combinatorial regulation and for building

37 raph diffusion kernel as a unified framework for inferring complex/pathway membership analogous to "f

38 NP-SEQ is a statistical model-based approach for inferring copy number profiles directly from high-co

39 arkov Models (HMM) to analyze SNP array data for inferring copy numbers and loss-of-heterozygosity (L

40 Although there are many methods available for inferring copy-number variants (CNVs) from next-gene

41 OV) which combines three distinct approaches for inferring covariation signals from multiple sequence

42 we demonstrate the usefulness of the method for inferring demographic history, especially recent cha

43 We propose a hierarchical Bayesian model for inferring differences between groups of samples more

44 the existence of many programs and databases for inferring different protein functions, a pipeline th

45 Here we present a general method for inferring direct effects from an observed correlatio

46 only validate our widely-applicable approach for inferring directed genotype networks from data, but

47 fers to a family of computational techniques for inferring disease genes through a set of training ge

48 xplanation space to be particularly valuable for inferring disease subtypes, the method is more gener

49 These detailed data have been proven useful for inferring disease transmission to a more refined lev

50 mirConnX is a user-friendly web interface for inferring, displaying and parsing mRNA and microRNA

51 Here we introduce a framework for inferring DNA-binding specificities by considering p

52 Methods for inferring dominance hierarchies are relatively robus

53 We present MDSINE, a suite of algorithms for inferring dynamical systems models from microbiome t

54 We then describe a new method for inferring each individual's germline gene set from d

55 We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is

56 ance of quantitative seasonal abundance data for inferring ecological distributions and demonstrate s

57 dy, we test the suitability of these methods for inferring ecological interactions by constructing ne

58 Here we describe a procedure for inferring eye position using multi-electrode array r

59 Conventional methods for inferring FOI estimate a time-averaged value and are

60 Thus methods for inferring [Formula: see text] and the degree of hete

61 This has broad implications for inferring function from the presence of structurally

62 er 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where

63 We compare phylogenetic approaches for inferring functional gene links.

64 irst is a computationally inexpensive method for inferring functional information from protein crysta

65 We describe a novel approach for inferring functional relationship of proteins by det

66 The database can also be used for inferring functionality, which for membrane proteins

67 ted parsimony and maximum likelihood methods for inferring gain and loss events.

68 ssociated genes, better than popular methods for inferring gene expression networks.

69 ns, and (3) developed an efficient algorithm for inferring gene expression rate constants from the mo

70 itance, operon and gene fusion-based methods for inferring gene function and reconstructing cellular

71 genetic screens provide a powerful approach for inferring gene function on the basis of the phenotyp

72 , we present GINI, a machine learning system for inferring gene interaction networks from Drosophila

73 ntal data are a valuable, but limited source for inferring gene regulation mechanisms on a genomic sc

74 ic evaluation of state-of-the-art algorithms for inferring gene regulatory networks from single-cell

75 ing of transcriptional regulation as well as for inferring gene regulatory networks.

76 propose an improved gene clustering approach for inferring gene signaling pathways from gene microarr

77 Most methods for inferring gene-gene interactions from expression dat

78 he differences that do exist are informative for inferring general principles about the holistic evol

79 efrontal cortex (VMPFC) activation increased for inferring generous play and decreased for inferring

80 ful for identifying an appropriate technique for inferring genetic networks and for interpreting the

81 We have developed and implemented a method for inferring genetic regulatory networks for time serie

82 approach is a model-based imputation method for inferring genotypes at observed or unobserved SNPs,

83 ly Bayesian approaches (originally developed for inferring geographic spread and rates of molecular e

84 ications for sawfish conservation as well as for inferring habitat residency of euryhaline elasmobran

85 ently selected alleles, eliminating the need for inferring haplotype.

86 three previously published Bayesian methods for inferring haplotypes from genotype data in a populat

87 we believe that polyHap, our proposed method for inferring haplotypic phase from genotype data, will

88 an overgeneralization of adaptive mechanisms for inferring harmful intentions and the ability to caus

89 We present a new method for inferring hidden Markov models from noisy time seque

90 Here we present a general technique for inferring hierarchical structure from network data a

91 There are many methods for inferring hierarchies from social interactions.

92 archy affect the performance of five methods for inferring hierarchies, (2) propose an amendment that

93 EBEN provides a useful tool for inferring high-dimensional sparse model in multiple

94 on penalties in the most widely used methods for inferring homology by sequence alignment, including

95 Our model improves on previous approaches for inferring host mortality from parasite abundance dat

96 Our results illustrate a general method for inferring how groups of neurons work together to mod

97 These results may be useful for inferring how thermal alteration of soil by wildfire

98 d assessed multiple computational approaches for inferring human biology from mouse datasets.

99 technology has provided a great opportunity for inferring human demographic history by investigating

100 macrophage model of infection is unsuitable for inferring human-relevant differences in nontyphoidal

101 As genetic datasets grow, methods for inferring IBD segments that scale well will be criti

102 as well as in defining computational methods for inferring (imputing) unknown interactions.

103 We present a novel approach for inferring influence of a rare stressor on a rare spe

104 rdiffusive motion, is of particular interest for inferring information about the dynamics of the cyto

105 ids was recently introduced as a useful tool for inferring information on such correlated sites.

106 but although many methods have been proposed for inferring integer copy number, few have been designe

107 e capacity for curiosity and exploration and for inferring internal models of the external world.

108 , we present OncoNEM, a probabilistic method for inferring intra-tumor evolutionary lineage trees fro

109 ch as approximate Bayesian computation (ABC) for inferring invasion history.

110 on of a protein has become a useful practice for inferring its function.

111 dysregulation and has important implications for inferring ketamine's mechanism of action from studie

112 o (semi)-unsupervised data-driven approaches for inferring latent structures that may give insight in

113 Furthermore, we propose methods for inferring LD-decay rates and recombination hotspots

114 applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor tra

115 s them in a single report, which can be used for inferring likely causal genes.

116 Many software packages are available for inferring local ancestry in admixed individuals.

117 We present a new haplotype-based approach for inferring local genetic ancestry of individuals in a

118 MAP, ancestry of Modern Admixed Populations) for inferring local phased ancestry.

119 population and subsequently develop a method for inferring location to a finer scale.

120 ogeneous Bayesian analysis of variance model for inferring loci involved in recent selective sweeps b

121 ate and more efficient than existing methods for inferring locus-specific ancestries, enabling it to

122 working clinician and their predictive power for inferring long term viral eradication from short ter

123 hlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

124 pproach is the use of computational modeling for inferring mechanisms which generate observed behavio

125 trol methods, and provides a powerful method for inferring mechanistic relationships underlying biolo

126 moother procedure provides a powerful method for inferring melt rates in a warming world.

127 em (MNS) and some a mentalizing system (MZS) for inferring mental states.

128 tudies of Buchnera have provided a new means for inferring metabolic capabilities of the symbionts an

129 easuring macro- and mesoscopic structure and for inferring microstructural properties; we also descri

130 Admixed populations have been used for inferring migrations, detecting natural selection, a

131 Here, we present a method for inferring missing CNV genotypes, predicting CNV alle

132 We propose a framework for inferring models of tumor progression from single-ce

133 Quantitative microscopy is a valuable tool for inferring molecular mechanisms of cellular processes

134 Implications for inferring molecular mechanisms of solvent effects on

135 e developed an integrated, scalable strategy for inferring multiple human gene interaction types that

136 We present a method for inferring mutation and gene-conversion rates by usin

137 velop a novel Bayesian statistical framework for inferring natural selection at a pair of linked loci

138 3D genome which may provide key information for inferring neoantigens' immunogenicity.

139 werful experimental-computational technology for inferring network models that predict the response o

140 ruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutua

141 rrelational methods are increasingly popular for inferring networks from co-occurrence and time serie

142 optical signals have yielded various metrics for inferring neural connectivity, and hence for mapping

143 (P <10(-4)), properties that were important for inferring new candidate interactions.

144 principle demonstration of a novel framework for inferring, noninvasively, neuromodulatory influences

145 Although several algorithms for inferring nucleosome position from a single experime

146 It also proves useful for inferring numbers of secondary infections and identi

147 One useful strategy for inferring others' mental states (i.e., mentalizing)

148 Statistical methods for inferring parameters such as the recombination rate

149 While methods for inferring parental haplotype assignments on large F1

150 ause it has been shown that they can be used for inferring participation in a study if the individual

151 However, current approaches for inferring past migration episodes in the fields of a

152 We present a novel method for inferring patient-specific genetic activities incorp

153 We propose a computational framework for inferring phenotypic crosstalk (PHOCOS) that is suit

154 ggesting that these loci are not appropriate for inferring phylogenetic relationships among species.

155 ere, we present a novel computational method for inferring phylogenetic relationships from partial se

156 We present a statistical method for inferring phylogenetic trees from EST-based incomple

157 termining the molecular basis of adaptation, for inferring phylogenies and for engineering novel prot

158 sure and fast running time make MulRF useful for inferring phylogenies from large collections of gene

159 o propose a natural graphical representation for inferring phylogenies.

160 esent a principled likelihood-based approach for inferring physical models of TF-DNA binding energy f

161 ially offer a powerful statistical framework for inferring population genetic parameters.

162 led to the development of new methodologies for inferring population history and refuelled the debat

163 dicate that the modified SG method is useful for inferring positive selection at codon sites where ne

164 terns to identify spatially similar patterns for inferring potential genetic interactions.

165 A web application for inferring potentially stabilizing non-bonding intera

166 These results are fundamental for inferring processes on Earth and other planets from

167 understanding the dynamics of adaptation and for inferring properties of an organism's fitness landsc

168 A large literature exists for inferring/proposing biological pathways/networks usi

169 We present an algorithm for inferring protein complexes from weighted interactio

170 into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and the

171 ervation is an important, established method for inferring protein function, modularity and specifici

172 arities between proteins is often unreliable for inferring protein function.

173 in subcellular localization is indispensable for inferring protein functions.

174 the usefulness of order/disorder predictions for inferring protein structure from sequence.

175 Molecular biomarkers hold promise for inferring rates of key metabolic activities in compl

176 Current estimation techniques for inferring reaction rates frequently rely on marginal

177 n widely applied population genetics methods for inferring recombination rates, for detecting selecti

178 SHUS, that implements three exact algorithms for inferring regions of hemizygosity containing genomic

179 In this paper, we present a novel framework for inferring regulatory and sequence-level information

180 Based on our empirical criteria for inferring regulatory effects (presence-absence of sp

181 h motifs in genome sequences is a major goal for inferring regulatory networks yet has been hampered

182 e basal tracheophyte genome, which is useful for inferring relationships among bryophyte lineages.

183 to stimulate development of analytical tools for inferring relationships between somatic changes and

184 actions (i.e. sampling effort) are necessary for inferring reliable dominance hierarchies, nor are th

185 We present a maximum likelihood method for inferring reticulate evolutionary histories while ac

186 monstrate that BIC provides a good framework for inferring reticulate evolutionary histories.

187 tic variants as valid instrumental variables for inferring risk factors causing coronary artery disea

188 t software implementing a model-based method for inferring ROH in genome-wide SNP datasets that incor

189 DupTree is a new software program for inferring rooted species trees from collections of g

190 ocessing are of interest to forensic science for inferring sample provenance.

191 y, we discuss challenges and recommendations for inferring selection on introgressed regions.

192 ed for inferring generous play and decreased for inferring selfish play.

193 Here we propose a method for inferring sets of biochemical rate constants that go

194 nt DyStruct, a model and inference algorithm for inferring shared ancestry from temporally sampled ge

195 ession for Signaling Determination (DESIDE), for inferring signaling activity from microarray measure

196 A variety of techniques exist for inferring signaling pathways.

197 p and protein modification are indispensable for inferring signalling pathways from PPI networks.

198 ween protein sequences that can be important for inferring similarity of structure or function.

199 ch techniques demonstrate high success rates for inferring 'simple' genomic segments, they are confou

200 cleotide substitutions, a learning algorithm for inferring site-specific substitution biases directly

201 The proposed framework is useful for inferring small NM-based modules of TF-target gene r

202 We discuss different approaches for inferring social networks from these data and displa

203 Here, we develop a method for inferring some aspects of the order of mutational ev

204 C) model has emerged as a powerful framework for inferring species phylogenies while accounting for a

205 ing species tress) is a new software package for inferring species trees while accommodating uncertai

206 ifying downstream snapshot measures required for inferring specific dynamical features of upstream si

207 We derive a general Bayesian framework for inferring statistically optimized atomic potentials

208 unodeficiency virus type 1 (HIV-1) is useful for inferring structural and/or functional constraints a

209 tumor Evolution), a new probabilistic method for inferring subclonal history and lineage tree reconst

210 Recently, tools and methods for inferring such gene sequences from AIRR-seq datasets

211 Here, we present a general framework for inferring such histories and demonstrate how it can

212 We propose a new algorithmic method for inferring such interactions between genes using data

213 ding influences gene expression is important for inferring target genes from TF chromatin immunopreci

214 We present a new tool, PAREameters, for inferring targeting criteria from small RNA and degr

215 novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental condi

216 Our results provide a physical basis for inferring that greenhouse warming is likely to contr

217 any particular season is an unreliable basis for inferring that the year-round average kill rate woul

218 We describe a machine-learning approach for inferring the activity levels of all unexplored sing

219 Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data

220 lele age estimates to power a rapid approach for inferring the ancestry shared between individual gen

221 We present SVclone, a computational method for inferring the cancer cell fraction of structural var

222 have taken advantage of a combined approach for inferring the causes of range limits.

223 ak repair (HDR) functional assay as a method for inferring the clinical relevance of VUS in the DBD o

224 the multiple sequence alignment of a protein for inferring the co-evolutionary sectors.

225 oPlotter, an unbiased segmentation algorithm for inferring the compositional organization of genomes.

226 dentifying ancestry components correctly and for inferring the correct tree.

227 ns and apes may provide valuable information for inferring the demographic history of these species,

228 Recently, methods have been developed for inferring the DFE that use information from the alle

229 informed choice of outgroup species suitable for inferring the directions of changes, including testi

230 an pre-implantation development is essential for inferring the earliest cell fate decisions.

231 . sinense genome provides a unique reference for inferring the early evolution of eudicots and the me

232 90, Jotun Hein proposed using this criterion for inferring the evolution of sequences subject to reco

233 with diverse evolutionary models, a pipeline for inferring the evolutionary history of a gene family

234 algorithms, we built an integrated pipeline for inferring the evolutionary history of a given gene f

235 tionary alignment modeler, called "Ortheus," for inferring the evolutionary history of a multiple ali

236 An important objective for inferring the evolutionary history of gene families

237 Here, we propose Canopy, a method for inferring the evolutionary phylogeny of a tumor usin

238 We develop an approach for inferring the fractional fire contribution to ambien

239 ac Ca2+ release process and a general method for inferring the functional properties of transmembrane

240 (PANTHER) is a comprehensive software system for inferring the functions of genes based on their evol

241 a an unsupervised machine learning algorithm for inferring the gene targets of sets of TF binding sit

242 easonal migration has long posed a challenge for inferring the geographic origins of migratory specie

243 , and uses less memory than existing methods for inferring the human genome at high resolution (10 kb

244 We also develop a method for inferring the largest common sub-paths within each o

245 t the value of using modern humans as models for inferring the limits of hominin arboreality.

246 We present a method for inferring the mechanism most accurately capturing a

247 overcome this problem with a novel framework for inferring the metabolic functions of a cell before m

248 mptions leads to similar solution strategies for inferring the model parameters in both variable type

249 robust, efficient, assumption-free approach for inferring the molecular mechanisms that underlie the

250 al areas, it also has important implications for inferring the nature and epidemiological consequence

251 ter estimation and model selection technique for inferring the number and configuration of promoter s

252 For inferring the number of individual gene loss or gain

253 ian model comparison then provides machinery for inferring the optimal order over the group of subjec

254 Here, we discuss two criteria for inferring the optimal tree topology from data sets w

255 We then propose a method for inferring the order of fate decisions.

256 s is an essential tool of classical genetics for inferring the order of function of genes in a common

257 ation, we have developed an automatic method for inferring the origins of DBD families and their spec

258 his paper is to develop efficient algorithms for inferring the parameters of a general class of Gauss

259 PopABC is a computer package for inferring the pattern of demographic divergence of c

260 t a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by ide

261 logy-based phylogeny for the genus Gallotia, for inferring the phylogenetic position of extinct speci

262 We present a Bayesian method for inferring the phylogenetic relationship among relate

263 le to the number of synonymous substitutions for inferring the phylogenetic tree in the SG method, an

264 characters of each type that have been used for inferring the phylogeny of mammals, we find that on

265 this new tool is fast in speed and accurate for inferring the phylogeny of organisms.

266 for identifying the optimal feature lengths for inferring the phylogeny of prokaryotes, strictly spe

267 rate an ST, which results in a powerful tool for inferring the population structure of this pathogen,

268 studies mapping genotypes to phenotypes and for inferring the power of natural selection in human hi

269 with respect to alternative parsimony rules for inferring the presence of precursor architectures in

270 new, to our knowledge, method developed here for inferring the principal curves.

271 e Gibbs sampler is described, and procedures for inferring the probability of yet to be observed futu

272 sts, we also developed an in silico approach for inferring the relative impact of a mutation on RC ba

273 We report a new method for inferring the scaled mutation rate, theta = 2Neu, an

274 promising two-dimensional chemical strategy for inferring the secondary and tertiary structures that

275 We present a new method for inferring the SFS using one or two outgroups that at

276 ly, I use the distance-based Bayesian method for inferring the single most likely ancestral codon fro

277 flexible and computationally feasible method for inferring the sources of aneuploidy is thus crucial.

278 Here, we developed and validated a method for inferring the spatial organization of sequential bio

279 icle we present a novel computational method for inferring the strain tree despite massive gene tree

280 gnitude over the methods reported previously for inferring the structure of dynamic networks, such as

281 ases and provides a widely applicable method for inferring the underlying helicase kinetics from forc

282 mporal dynamics of brain activity is crucial for inferring the underlying synaptic and nonsynaptic me

283 d indicate that OFC is specifically required for inferring the value of expected outcomes.

284 This is evidence that the VMF is critical for inferring the value of whole objects in a multiattri

285 Several methods for inferring this parameter have been proposed, with di

286 Mathematical methods for inferring time to extinction have been widely applie

287 We propose a novel method for inferring transcriptional regulation using a simple,

288 Here, we develop a method for inferring translation elongation kinetics from ribos

289 egration of genomic and epidemiological data for inferring transmission chains.

290 (VNTR)-based clustering, it was insufficient for inferring transmission in the majority of cases.

291 study, we test previously described methods for inferring transmission stage investment against simu

292 direct transmission inference (DTI) problem for inferring transmission trees that support multi-stra

293 This work highlights a powerful technology for inferring transport function and quantifying nutrien

294 e.g., road kill) should be used with caution for inferring trophic ecology as decay can result in sig

295 implemented in publicly available software, for inferring tumor phylogenies on data from potentially

296 This argues that the VMF is critical for inferring value from configural information to guide

297 The orbitofrontal cortex (OFC) is necessary for inferring value in tests of model-based reasoning, i

298 ation for examining the accuracy of NJ trees for inferring very large phylogenies.

299 Here, we set out a novel approach for inferring viral transmission bottlenecks; our method

300 veloping statistical and computational tools for inferring 'who infected whom' in an infectious disea