ライフサイエンスコーパス: multiple sequence alignment

1 speed of BLAST and avoids the complexity of multiple sequence alignment.

2 lignment tool for membrane proteins based on multiple sequence alignment.

3 s and starting from a (typically very large) multiple sequence alignment.

4 utionary analyses are based on pre-estimated multiple sequence alignment.

5 on events and relies on a fixed, precomputed multiple sequence alignment.

6 of members, without the need for an initial multiple sequence alignment.

7 vailable software, and it does not require a multiple sequence alignment.

8 terms, including for example an interactive multiple sequence alignment.

9 th the local and global quality of the input multiple sequence alignment.

10 m either a matrix-like array of numbers or a multiple-sequence alignment.

11 ighly conserved sites, and rely heavily upon multiple sequence alignments.

12 ce databases and to create potentially large multiple sequence alignments.

13 maximum likelihood methods from good quality multiple sequence alignments.

14 tention in recent years as an alternative to multiple sequence alignments.

15 d solely on correlated mutations detected in multiple sequence alignments.

16 WYSIWYG editing, analysis and annotation of multiple sequence alignments.

17 to create new sequence- and structure-based multiple sequence alignments.

18 ral methods for the evolutionary analysis of multiple sequence alignments.

19 e constraints to construct consistency-based multiple sequence alignments.

20 e of non-coding genes can be detected within multiple sequence alignments.

21 equences, graphical secondary structures and multiple sequence alignments.

22 r RNA secondary structure conformations from multiple sequence alignments.

23 e groups of related targets based on complex multiple sequence alignments.

24 ific symbol compositions between two sets of multiple sequence alignments.

25 ive web-based viewer to display pre-computed multiple sequence alignments.

26 y other built-in tools that can help analyze multiple sequence alignments.

27 ities of TurboFold by additionally providing multiple sequence alignments.

28 that it performs as well as methods based on multiple sequence alignments.

29 be exploited to improve the quality of large multiple sequence alignments.

30 c profile, the list of member proteins and a multiple sequence alignment, a statistical summary and g

31 r ATGC-COGs (Clusters of Orthologous Genes), multiple sequence alignments, a set of 'index' orthologs

32 o the divergence of functional lineages in a multiple sequence alignment-a model for how sector prope

33 While most of the recent improvements in multiple sequence alignment accuracy are due to better u

34 nted a thorough quality control procedure on multiple sequence alignments, aiming to provide minimum

35 sidues forming the IC pockets, together with multiple sequence alignments, allowed us to propose a fu

36 ven a set of sequences SARA-Coffee outputs a multiple sequence alignment along with a reliability ind

37 Multiple sequence alignment, although dominantly used by

38 Multiple sequence alignment analysis suggested that RIP1

39 P domains were detected in these proteins by multiple sequence alignment analysis.

40 he model dynamics on parameters derived from multiple sequence alignments analyzed by using direct co

41 The net result is both a multiple sequence alignment and a hierarchical clusterin

42 ts, in which each family is represented by a multiple sequence alignment and a profile hidden Markov

43 , non-protein-coding RNAs, transcribed RNAs, multiple sequence alignment and evolutionarily constrain

44 our additional B2 elements we generated a B2 multiple sequence alignment and identified a shared, deg

45 llows the user to submit a query sequence or multiple sequence alignment and perform the search in a

46 ein sequence, gathers homologs, constructs a multiple sequence alignment and phylogenetic tree and fi

47 rent methods that are available are based on multiple sequence alignment and phylogenetic tree constr

48 existing software for sensitive and accurate multiple sequence alignment and profile-profile comparis

49 omatically collects homologues, infers their multiple sequence alignment and reconstructs a phylogene

50 , error correction of sequencing reads, fast multiple sequence alignment and repeat detection.

51 models for annotating structured features in multiple sequence alignments and analyzing the evolution

52 protein domains and families, represented as multiple sequence alignments and as profile hidden Marko

53 three-dimensional structural information or multiple sequence alignments and can even predict small

54 ing pleas for methods to assess whole-genome multiple sequence alignments and compare the alignments

55 ion of RNA sequence families, represented by multiple sequence alignments and covariance models (CMs)

56 ved Domain Database (CDD) is a collection of multiple sequence alignments and derived database search

57 from image recognition databases and protein multiple sequence alignments and discuss possible interp

58 r-friendly webpages are available, including multiple sequence alignments and HMM profiles for each V

59 The construction of multiple sequence alignments and inference of huge phylo

60 for machine learning, including high-quality multiple sequence alignments and insulated training/vali

61 ally improves both its utility in generating multiple sequence alignments and its heuristic utility.

62 As in previous versions, eggNOGv4 provides multiple sequence alignments and maximum-likelihood tree

63 omology between protein sequences, rely upon multiple sequence alignments and phylogenetic trees of l

64 ence protein sequences can be analysed using multiple sequence alignments and phylogenetic trees.

65 es the wealth of information associated with multiple sequence alignments and presents them in an int

66 Here, multiple sequence alignments and secondary structure pre

67 s pipeline results in significantly improved multiple sequence alignments and SNP identifications whe

68 of TRAP and TEN across species, we performed multiple sequence alignments and statistical coupling an

69 ionships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hid

70 genes are represented in phylogenetic trees, multiple sequence alignments and statistical models (hid

71 erate gold standard alignments for improving multiple sequence alignments and transferring functional

72 Through multiple-sequence alignment and statistical testing of e

73 tification of orthologous genes or proteins, multiple sequence alignment, and choice of substitution

74 subgenomes in existing databases, performs a multiple sequence alignment, and design primers based on

75 From these observations, multiple sequence alignment, and homology modeling, we c

76 The method takes as input a multiple sequence alignment, and outputs an accurate pos

77 database searching by hidden Markov models, multiple sequence alignment, and phylogenetic tree infer

78 ive cysteine ligands were identified using a multiple sequence alignment, and substitution of just on

79 us criteria and methods available to perform multiple sequence alignments, and among these, the minim

80 mic intervals, utilities for manipulation of multiple sequence alignments, and molecular evolution al

81 pairwise correlations between sites in deep multiple sequence alignments, and these pairwise couplin

82 etic trees can be produced in the absence of multiple sequence alignments, and we propose that these

83 nce-design constraints derived from antibody multiple-sequence alignments, and (ii) during backbone d

84 Multiple sequence alignments are a fundamental tool for

85 Multiple sequence alignments are essential in computatio

86 Multiple sequence alignments are essential in homology i

87 Accurate multiple sequence alignments are essential in protein st

88 olutionary constraint derived from mammalian multiple sequence alignments are strongly predictive of

89 We introduce ProfileGrids that represent a multiple sequence alignment as a matrix color-coded acco

90 detection of biological phenomena rely on a multiple sequence alignment as input.

91 This approach uses multiple-sequence alignments, atomic-resolution structur

92 nce realignment tool that can refine a given multiple sequence alignment based on suboptimal alignmen

93 een shown to produce results as effective as multiple-sequence alignment based methods for reconstruc

94 d specificity up to 85%), as compared with a multiple sequence alignment-based method (sensitivity 57

95 ross selections of genomes and finally build multiple sequence alignments between Protein Data Bank (

96 Based on multiple-sequence alignments between permease orthologs,

97 searches of NCBI and local databases, create multiple sequence alignments, build phylogenetic trees,

98 generate suboptimal alignments from an input multiple sequence alignment by a probabilistic sampling

99 nts a new algorithm, REFINER, that refines a multiple sequence alignment by iterative realignment of

100 it is mere common sense that inaccuracies in multiple sequence alignments can have detrimental effect

101 Multiple sequence alignment combined with comparative st

102 t sequencing reads, ortholog identification, multiple sequence alignment, concatenation, phylogenetic

103 aches for inferring covariation signals from multiple sequence alignments, considers a broad range of

104 zation and analysis JavaScript component for Multiple Sequence Alignment data of any size.

105 writing different sequence file formats and multiple sequence alignments, dealing with 3D macro mole

106 milarity search (e.g. FASTA and NCBI BLAST), multiple sequence alignment (e.g. Clustal Omega and MUSC

107 We report a method based on analysis of multiple sequence alignments, embodied in our program Ja

108 Genome assembly, repeat detection, multiple sequence alignment, error detection and many ot

109 ect to create large, diverse and informative multiple sequence alignments for a test set of 1656 know

110 dure that uses a genetic algorithm to search multiple sequence alignments for evidence of recombinati

111 Probalign computes maximal expected accuracy multiple sequence alignments from partition function pos

112 cleotide polymorphism (SNP) prediction using multiple sequence alignments from re-sequencing data.

113 Multiple sequence alignments from the venom gland transc

114 tistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular se

115 The latter can be calculated from the multiple sequence alignments generated by PSI-BLAST.

116 nce models (CMs) from structurally annotated multiple sequence alignments given as input.

117 most common amino acid in each position of a multiple sequence alignment, has proven to be an efficie

118 Multiple sequence alignments have become one of the most

119 Multiple sequence alignments have been constructed acros

120 der of sequence alignment in the progressive multiple sequence alignment heuristic.

121 ase catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and

122 A previous Dbf4p multiple sequence alignment identified a conserved appro

123 en given to the problem of creating reliable multiple sequence alignments in a model incorporating su

124 hat analyzes correlated mutation patterns in multiple sequence alignments in order to predict disulfi

125 Multiple sequence alignments indicate that a surface on

126 ructure suggests these are noncatalytic, and multiple-sequence alignments indicate that they are uniq

127 Multiple sequence alignment indicated that these trGTPas

128 Multiple-sequence alignment indicates the active site Ly

129 t can inter-residue contact predictions from multiple sequence alignments, information which is ortho

130 Multiple sequence alignment is a basic part of much biol

131 Multiple sequence alignment is a cornerstone of comparat

132 Multiple sequence alignment is a difficult computational

133 Multiple sequence alignment is a fundamental task in bio

134 Multiple sequence alignment is an important tool to unde

135 A multiple sequence alignment is obtained from these proba

136 However, accurate large-scale multiple sequence alignment is very difficult, especiall

137 Evolutionary information encoded in multiple sequence alignments is known to greatly improve

138 h to describe couplings between columns in a multiple sequence alignment it is possible to significan

139 Given either a single protein sequence or a multiple sequence alignment, Jpred derives alignment pro

140 ions, including analyses at the whole genome multiple sequence alignment level.

141 We present UPP, a multiple sequence alignment method that uses a new machi

142 is much faster than the widely acknowledged multiple sequence alignment method.

143 e generally more accurate than other leading multiple sequence alignment methods (i.e. Probcons, MAFF

144 p between fast clustering methods and slower multiple sequence alignment methods and provides a seaml

145 Traditional multiple sequence alignment methods disregard the phylog

146 We propose a multiple sequence alignment (MSA) algorithm and compare

147 le regions of rRNA genes than do traditional multiple sequence alignment (MSA) approaches.

148 Accurate tools for multiple sequence alignment (MSA) are essential for comp

149 y areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for vario

150 d efficient pipeline available for sensitive multiple sequence alignment (MSA) collection.

151 We characterize pairwise and multiple sequence alignment (MSA) errors by comparing tr

152 ee reconstruction requires construction of a multiple sequence alignment (MSA) from sequences.

153 siblast PSSMs are built from the query-based multiple sequence alignment (MSA) implied by the pairwis

154 Multiple sequence alignment (MSA) is a core method in bi

155 While multiple sequence alignment (MSA) is a potent tool to de

156 Multiple sequence alignment (MSA) is a prominent method

157 A challenge in multiple sequence alignment (MSA) is that the alignment

158 JABAWS:MSA provides services for five multiple sequence alignment (MSA) methods (Probcons, T-c

159 We present a parsimonious, structure-based multiple sequence alignment (MSA) of 497 human protein k

160 in sequence profiles, which are derived from multiple sequence alignment (MSA) of sequence homologs i

161 lated format and in the form of an annotated multiple sequence alignment (MSA) that may be edited int

162 chain Monte Carlo (MCMC) sampler for protein multiple sequence alignment (MSA) that, as implemented i

163 l key factors [i.e. deep learning technique, multiple sequence alignment (MSA), distance distribution

164 ions remain due to the requirement for large multiple sequence alignments (MSA) and the fact that, in

165 etermine protein structure and function from Multiple Sequence Alignments (MSA) are emerging as power

166 cus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of

167 nt Space Termination) algorithm for creating multiple sequence alignments (MSA).

168 erver for simultaneous estimation of protein multiple sequence alignments (MSAs) and phylogenetic tre

169 st commonly used method for visualization of multiple sequence alignments (MSAs) and sequence motifs.

170 entire length of a gene are ideally used for multiple sequence alignments (MSAs) and the subsequent i

171 Multiple Sequence Alignments (MSAs) are a fundamental op

172 Multiple sequence alignments (MSAs) are a prerequisite f

173 Multiple sequence alignments (MSAs) are at the heart of

174 Although multiple sequence alignments (MSAs) are essential for a

175 Multiple sequence alignments (MSAs) are usually scored u

176 ensional (3D) structures to high-quality RNA multiple sequence alignments (MSAs) from diverse biologi

177 The generation of multiple sequence alignments (MSAs) is a crucial step fo

178 Reconstruction of multiple sequence alignments (MSAs) is a crucial step in

179 ing rational and systematic information from multiple sequence alignments (MSAs) is becoming increasi

180 arison of evolutionary patterns reflected in multiple sequence alignments (MSAs) of protein families.

181 e covariance matrix (or precision matrix) of multiple sequence alignments (MSAs) through deep residua

182 e by identifying correlated mutations within multiple sequence alignments (MSAs), most commonly throu

183 niclust50, Uniclust30 and three databases of multiple sequence alignments (MSAs), Uniboost10, Uniboos

184 ments (PWAs) and some typical types of local multiple sequence alignments (MSAs), we numerically comp

185 Highly divergent sites in multiple sequence alignments (MSAs), which can stem from

186 ion methods rely on the availability of deep multiple sequence alignments (MSAs).

187 at exploits the information in large diverse multiple sequence alignments (MSAs).

188 ment construction based on the comparison of multiple sequence alignments (MSAs).

189 the specific choice of homologs included in multiple sequence alignments (MSAs).

190 ng Analysis (DCA) of correlated mutations in multiple sequence alignments (MSAs).

191 utionary relationships between residues from multiple sequence alignments (MSAs).

192 Multiple sequence alignment of 143 RodZ sequences from s

193 f whole-genome (genic + nongenic) sequences, multiple sequence alignment of a few selected genes is n

194 stinguishing consensus topology generated by multiple sequence alignment of a group of neurons reveal

195 The package only requires the multiple sequence alignment of a protein for inferring t

196 Multiple sequence alignment of AdRSZ21 with putative ort

197 We also performed a multiple sequence alignment of confirmed replicators on

198 imine cross-link by electrophoresis, MS, and multiple sequence alignment of de novo transcriptome and

199 A multiple sequence alignment of diverse ROK family member

200 conserved domain identified in this study by multiple sequence alignment of DYX1C1 proteins recovered

201 utagenesis strategy for Lfng was guided by a multiple sequence alignment of Fringe proteins and solut

202 ethods to extract amino acid contacts from a multiple sequence alignment of homologues of the curli s

203 Global pairwise and multiple sequence alignment of neurite topologies enable

204 Based on a multiple sequence alignment of PduX homologues and other

205 Multiple sequence alignment of several HCMV IE86 homolog

206 ation of the structure in conjunction with a multiple sequence alignment of the clip domains from dif

207 Multiple sequence alignment of the helicase-related regi

208 lutionary profile is then constructed from a multiple sequence alignment of the interface analogies,

209 Multiple sequence alignments of all structurally charact

210 tron structures; (iii) graphical analysis of multiple sequence alignments of amino acid and coding nu

211 patterns of amino acid coevolution in large, multiple sequence alignments of cognate kinase-regulator

212 Multiple sequence alignments of each orthologous intron

213 Multiple sequence alignments of evolutionarily distant p

214 Hidden Markov models (HMMs), which represent multiple sequence alignments of homologous proteins.

215 ies of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can

216 e datasets from various sources and generate multiple sequence alignments of identified clusters.

217 nation of this structure in conjunction with multiple sequence alignments of MPT64 homologs identifie

218 Using multiple sequence alignments of protein domains in the h

219 n Database (CDD) consists of a collection of multiple sequence alignments of protein domains that are

220 tion and coevolution profiles extracted from multiple sequence alignments of protein families with th

221 Accurate multiple sequence alignments of proteins are very import

222 ormative features that can be extracted from multiple sequence alignments of putative homologous gene

223 n to the final predicted 3D structure: three multiple sequence alignments of putative homologs using

224 If two multiple sequence alignments of related proteins are inp

225 Multiple sequence alignments of the CPSGs with sequences

226 Comprehensive multiple sequence alignments of the multisubunit DNA-dep

227 e involves concatenating several alternative multiple sequence alignments of the same sequences, prod

228 mes, the generation of reference-free Cactus multiple sequence alignments of these genomes, and the d

229 d a comparative, annotated, structure-based, multiple-sequence alignment of R2 subunits, identified a

230 Multiple-sequence alignment of the members of the (R)-hy

231 A multiple-sequence alignment of this family with Hsp100 p

232 Multiple-sequence alignments of A19 homologs indicated c

233 which is an incremental method for building multiple sequence alignments one match at a time.

234 tadata-driven statistical sequence analysis, multiple sequence alignment, phylogenetic tree construct

235 th a host of other analysis features such as multiple sequence alignments, phylogenetic analyses and

236 gene annotations, homologous gene families, multiple sequence alignments, phylogenetic trees, and co

237 Each family is represented by a multiple sequence alignment, predicted secondary structu

238 Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of struc

239 ts computational counterpart is known as the multiple sequence alignment problem.

240 ely related genomes requires (1) an accurate multiple sequence alignment program and (2) a method to

241 Multiple sequence alignment programs are an invaluable t

242 Multiple sequence alignment programs tend to reach maxim

243 ignificance of structured RNA predicted from multiple sequence alignments relies on the existence of

244 eals that constructing accurate whole-genome multiple sequence alignments remains a significant chall

245 nserved across eubacterial phyla, we created multiple sequence alignments representing 10 of these me

246 From a multiple sequence alignment, residues in surface-affixin

247 A multiple sequence alignment revealed that MXPyV is a clo

248 Analysis of multiple sequence alignments revealed that residues equi

249 sharing the same domain architecture, MUSCLE multiple sequence alignment, SATCHMO simultaneous alignm

250 The RNA 3D Structure-to-Multiple Sequence Alignment Server (R3D-2-MSA) is a new

251 Multiple sequence alignments show that residues in the d

252 Multiple sequence alignment showed high conservation of

253 Multiple sequence alignments showing conserved residues

254 A multiple sequence alignment shows that these three cruci

255 tational methods for the curation of quality multiple sequence alignments since these public datasets

256 mentary information includes sample lists of multiple sequence alignment software and sample screensh

257 Using profile searches followed by multiple sequence alignment, structure prediction and do

258 This includes methods for multiple sequence alignment, substitution model selectio

259 Additional information includes multiple sequence alignments, tab-separated files of fun

260 conformations for each modelled loop, and a multiple sequence alignment that incorporates the query

261 A-Bruijn Alignment (ABA) is a method for multiple sequence alignment that represents an alignment

262 cadherins to identify conserved positions in multiple sequence alignments that appear to be crucial d

263 ing analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify g

264 Given a multiple sequence alignment, the model uses Dirichlet mi

265 return alignments of query sequences against multiple sequence alignments; the redesign of the web pa

266 ics simulations, elastic network theory, and multiple sequence alignment to analyze the system.

267 used statistical analysis of the CFTR-ABCC4 multiple sequence alignment to identify the specific dom

268 ific score matrices (PSSMs) are derived from multiple sequence alignments to aid in the recognition o

269 n theory, Bayesian statistics, and PSI-BLAST multiple sequence alignments to predict the secondary st

270 MSAProbs is a state-of-the-art protein multiple sequence alignment tool based on hidden Markov

271 BCL::Align is a multiple sequence alignment tool that utilizes the dynam

272 the nucleosomal DNA is weak, and traditional multiple sequence alignment tools fail to yield meaningf

273 tron density and contact map visualizations, multiple sequence alignment tools for template-based mod

274 vices such as BLAST, FASTA, InterProScan and multiple sequence alignment tools such as ClustalW, T-Co

275 is able to improve the results from various multiple sequence alignment tools.

276 n updated human genome browser, a 44-species multiple sequence alignment track, improved variation an

277 expected accuracy optimization criterion for multiple sequence alignment uses pairwise posterior prob

278 We have created comprehensive multiple sequence alignments using all available sequenc

279 c trees generated from structurally informed multiple sequence alignments using both domain structura

280 annotation program JoY, formats a submitted multiple-sequence alignment using three-dimensional (3D)

281 to the sequence download options, and a new multiple sequence alignment viewer has been incorporated

282 group, a unique structure-based algorithm of multiple sequences alignment was developed.

283 for predicting protein functional sites from multiple sequences alignments was compared to 14 conserv

284 Using multiple sequence alignment, we conclude that similar fo

285 per, by analyzing amino acid covariance in a multiple sequence alignment, we have identified an energ

286 y interchanging specific sequence pairs in a multiple sequence alignment, we show that the functional

287 Finally, by multiple sequence alignments, we observe that G-quadrupl

288 as evolutionary information derived from the multiple sequence alignment were used as predictors.

289 Multiple sequence alignments were performed using MUSCLE

290 d the existence of an uncertainty induced by multiple sequence alignment when reconstructing phylogen

291 mlines this task by automatically generating multiple sequence alignments (where appropriate) and fin

292 ferent models of amino acid substitution and multiple sequence alignment which is an NP-hard problem

293 then compiled with the input sequence into a multiple sequence alignment which is mined for single-nu

294 Multiple sequence alignment, which is of fundamental imp

295 ccepted phylogenetic approaches are based on multiple sequence alignments, which analyze shared gene

296 el (HMM) to infer changes in phylogeny along multiple sequence alignments while accounting for rate h

297 By combining multiple sequence alignments with a previously determine

298 nted in SVG format with options to view full multiple sequence alignments with and without gaps and i

299 ser-friendly interface for manual editing of multiple sequence alignments with functions for input, e

300 r protein structure comparison, pairwise and multiple sequence alignments, working with DNA and prote