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

1 excluding residues with high variability in multiple sequence alignments).

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

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

4 s and starting from a (typically very large) 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 of sequences limits the application of local multiple sequence alignment.

9 ach protein sequence in order to improve the multiple sequence alignment.

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

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

12 maximum likelihood methods from good quality multiple sequence alignments.

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

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

15 es and at http://www.ebi.ac.uk/Tools/msa for 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 equences, graphical secondary structures and multiple sequence alignments.

21 r RNA secondary structure conformations from multiple sequence alignments.

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

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

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

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

26 te Cro proteins through manual inspection of multiple sequence alignments.

27 cation of the SCA, a statistical analysis of multiple sequence alignments.

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

29 ities of TurboFold by additionally providing multiple sequence alignments.

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

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

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

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

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

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

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

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

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

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

40 Multiple sequence alignment, although dominantly used by

41 Multiple sequence alignment analysis suggested that RIP1

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

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

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

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

46 sualization tools include Quality Screening, Multiple Sequence Alignment and Features and Annotations

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

48 ng only statistical information encoded in a multiple sequence alignment and no tertiary structure in

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

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

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

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

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

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

55 A combination of the concept of multiple sequence alignment and the 1-dimensional molecu

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

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

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

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

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

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

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

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

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

65 nhanced with a new search system, customized multiple sequence alignments and manipulation of protein

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

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

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

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

70 Here, multiple sequence alignments and secondary structure pre

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

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

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

74 Through multiple-sequence alignment and statistical testing of e

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

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

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

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

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

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

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

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 ns, a practical tool for progressive protein multiple sequence alignment based on probabilistic consi

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

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

95 Various multiple sequence alignment-based methods have been prop

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

97 Based on multiple-sequence alignments between permease orthologs,

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

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

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

101 n the set of bioactive compounds much like a multiple sequence alignment can isolate critical motifs

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

103 However, it is known that automatic multiple sequence alignments can often be improved by ma

104 Multiple sequence alignment combined with comparative st

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

106 Multiple sequence alignment, conformational clustering a

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

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

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

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

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

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

113 A D2-D10 expansion segments to hypothesize a multiple sequence alignment for major lineages of the hy

114 From the resulting sequences, we built a multiple sequence alignment for this domain family, whic

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

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

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

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

119 Multiple sequence alignments from the venom gland transc

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

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

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

123 Multiple sequence alignment has proven to be a powerful

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

125 Multiple sequence alignments have become one of the most

126 Multiple sequence alignments have been constructed acros

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

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

129 A previous Dbf4p multiple sequence alignment identified a conserved appro

130 positional correlation analysis for protein multiple sequence alignment in order to identify structu

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

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

133 Multiple sequence alignments indicate that a surface on

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

135 Multiple-sequence alignment indicates the active site Ly

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

137 Multiple sequence alignment is a basic part of much biol

138 Multiple sequence alignment is a cornerstone of comparat

139 Multiple sequence alignment is a difficult computational

140 Multiple sequence alignment is a fundamental task in bio

141 Evolutionary conservation estimated from a multiple sequence alignment is a powerful indicator of t

142 Multiple sequence alignment is an essential part of bioi

143 Multiple sequence alignment is an important tool to unde

144 A multiple sequence alignment is obtained from these proba

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

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

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

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

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

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

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

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

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

154 Traditional multiple sequence alignment methods disregard the phylog

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

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

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

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

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

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

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

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

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

164 Multiple sequence alignment (MSA) is a prominent method

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

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

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

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

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

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

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

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

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

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

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

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

177 Multiple sequence alignments (MSAs) are a prerequisite f

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

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

180 Multiple sequence alignments (MSAs) are usually scored u

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

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

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

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

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

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

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

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

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

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

191 ment construction based on the comparison of 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 oes not require subgroup definition, takes a multiple sequence alignment of a protein family as the o

196 Multiple sequence alignment of AdRSZ21 with putative ort

197 From functional analyses and a multiple sequence alignment of CmtR paralogs, M. tubercu

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

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

200 A multiple sequence alignment of diverse ROK family member

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

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

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

204 Multiple sequence alignment of more than 60 members of t

205 Global pairwise and multiple sequence alignment of neurite topologies enable

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

207 rganisms, biologists need accurate tools for multiple sequence alignment of protein families.

208 Multiple sequence alignment of several HCMV IE86 homolog

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

210 Multiple sequence alignment of the helicase-related regi

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

212 tion of elements under selective pressure in multiple sequence alignments of closely related genomes,

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

214 Multiple sequence alignments of each orthologous intron

215 Multiple sequence alignments of evolutionarily distant p

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

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

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

219 Using multiple sequence alignments of protein domains in the h

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

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

222 Accurate multiple sequence alignments of proteins are very import

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

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

225 If two multiple sequence alignments of related proteins are inp

226 n our tests, it discerned clustalw-generated multiple sequence alignments of signal recognition parti

227 Multiple sequence alignments of the CPSGs with sequences

228 Comprehensive multiple sequence alignments of the multisubunit DNA-dep

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 otein sequences, protein family assignments, multiple sequence alignments, phylogenies and functional

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

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

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

241 single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed seq

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

243 Multiple sequence alignment programs are an invaluable t

244 Multiple sequence alignment programs tend to reach maxim

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

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

247 onal QR factorization of numerically encoded multiple sequence alignments, removes redundancy from th

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

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

250 A multiple sequence alignment revealed that MXPyV is a clo

251 Analysis of multiple sequence alignments revealed that residues equi

252 Multiple-sequence alignment revealed two groups of EAL d

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

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

255 Multiple sequence alignments show that residues in the d

256 Multiple sequence alignments showing conserved residues

257 A multiple sequence alignment shows that these three cruci

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

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

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

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

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

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

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

265 inder) identifies regions of conservation in multiple sequence alignments that can serve as diagnosti

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

284 imation of insertion and deletion rates from multiple sequence alignments, using EM, under the single

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

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

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

288 Using multiple sequence alignment, we conclude that similar fo

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

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

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

292 Multiple sequence alignments were performed using MUSCLE

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

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