ライフサイエンスコーパス: for inferring

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

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

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

4 Many approaches for inferring adaptive molecular evolution analyze the u

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

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

7 lihood, and distance methods can all be used for inferring amino acid sequences of the proteins of an

8 rrangements has become a very powerful means for inferring ancient evolutionary relationships, since

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

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

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

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

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

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

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

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

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

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

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

20 e have exploited provides general principles for inferring catalytic activity from structural studies

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

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

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

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

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

26 of certain surrogate end points can be used for inferring clinically significant vaccine effects and

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

42 Methods for inferring dominance hierarchies are relatively robus

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

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

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

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

47 A new method is presented for inferring evolutionary trees using nucleotide sequen

48 We investigated the sample sizes required for inferring exclusion and linkage, for various combina

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

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

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

52 Interspecies comparison is a powerful tool for inferring function from genomic sequence and could u

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

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

55 We compare phylogenetic approaches for inferring functional gene links.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

71 erest in developing computational techniques for inferring genetic regulatory networks from whole-gen

72 sequence comparison is particularly powerful for inferring genome function and is based on the simple

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

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

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

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

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

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

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

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

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

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

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

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

85 m only a small representative set of species for inferring higher-level evolutionary history.

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

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

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

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

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

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

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

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

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

95 of 31 strains), but PCR-RFLP was more useful for inferring interstrain relatedness.

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

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

98 c variation along a chromosome may be useful for inferring its evolutionary history and for revealing

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

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

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

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

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

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

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

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

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

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

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

110 used to evaluate maximum likelihood methods for inferring male fertility in plant populations.

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

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

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

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

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

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

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

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

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

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

121 Implications for inferring molecular mechanisms of solvent effects on

122 recently been proposed as a powerful method for inferring molecular phylogenies, and it has been rep

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

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

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

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

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

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

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

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

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

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

133 en-18 isotope values of formation waters and for inferring paleotemperatures.

134 Statistical methods for inferring parameters such as the recombination rate

135 While methods for inferring parental haplotype assignments on large F1

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

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

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

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

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

141 amino acid sequences is a powerful approach for inferring phylogenetic relationships and for compari

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

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

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

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

146 o propose a natural graphical representation for inferring phylogenies.

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

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

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

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

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

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

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

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

155 al effects invalidates the standard approach for inferring properties of spontaneous mutation and nec

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

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

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

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

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

161 t relationships in novel sequences and hence for inferring protein function.

162 in subcellular localization is indispensable for inferring protein functions.

163 A computational method is proposed for inferring protein interactions from genome sequences

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

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

166 etween species and may, therefore, be useful for inferring recent selection.

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

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

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

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

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

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

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

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

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

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

177 Circles is a program for inferring RNA secondary structure using maximum weig

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

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

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

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

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

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

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

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

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

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

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

189 es at Parkfield, California, provide a means for inferring slip rate at depth throughout the active f

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

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

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

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

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

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

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

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

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

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

200 Based on conservative criteria for inferring synteny, "one to one correspondence" betwe

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

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

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

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

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

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

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

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

209 GENIE implements a statistical framework for inferring the demographic history of a population fr

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

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

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

213 90, Jotun Hein proposed using this criterion for inferring the evolution of sequences subject to reco

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

231 t suggest that this property would be useful for inferring the nature of linked selection either.

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

233 For inferring the number of individual gene loss or gain

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

249 population genetic models, it is also useful for inferring the replication mode of a virus.

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

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

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

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

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

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

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

257 boundary, the location of which is important for inferring the trajectories of 'suspect' terrain acro

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

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

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

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

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

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

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

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

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