ライフサイエンスコーパス: gene annotation

1 works, offering opportunities for regulatory gene annotation.

2 ty and compromising downstream steps such as gene annotation.

3 nctions is a powerful approach of functional gene annotation.

4 including the alignments of the hits to the gene annotation.

5 en clustered and filtered using the optional gene annotation.

6 level will substantially advance Arabidopsis gene annotation.

7 he training set based only on prior computer gene annotation.

8 eukaryotic genomes still benefit from manual gene annotation.

9 rams, and suggest corrections to improve the gene annotation.

10 ing and non-coding transcripts, facilitating gene annotation.

11 ow that functional modules can be useful for gene annotation.

12 genomes generated using multiple sources of gene annotation.

13 and to develop tools to predict 3'-ends for gene annotation.

14 s heavily on the completeness and quality of gene annotation.

15 ntial improvement of the currently available gene annotation.

16 ne finding to generate accurate and complete gene annotation.

17 k together to improve and extend the GENCODE gene annotation.

18 mblies and new expression data improving the gene annotation.

19 ng offers a promising solution for enhancing gene annotation.

20 R-RTs is critical for achieving high-quality gene annotation.

21 mputational analysis of mRNA-ends to improve gene annotation.

22 dance of genome alignment and independent of gene annotation.

23 isoforms from 44 968 gene models and updated gene annotation.

24 how proteogenomics can substantially improve gene annotation.

25 genes based on the recently released tomato gene annotation.

26 ed evidence codes, phenotype ontologies, and gene annotation.

27 ur approach does not depend on transcript or gene annotations.

28 f enrichment in sequencing reads relative to gene annotations.

29 gside foundation datasets, such as reference gene annotations.

30 ty that can be applied to assemblies lacking gene annotations.

31 aromyces pombe, independently from available gene annotations.

32 of processed pseudogene finding in mammalian gene annotations.

33 redictive accuracy analysis through verified gene annotations.

34 ression sequences to improve the accuracy of gene annotations.

35 ions greatly exceeds the number of validated gene annotations.

36 predicted ORFs that did not overlap WormBase gene annotations.

37 d to determine biological relevance from the gene annotations.

38 to provide direct experimental validation of gene annotations.

39 results of automated updates to Arabidopsis gene annotations.

40 s data visualization and curation of current gene annotations.

41 sed as the reference knowledgebase of fusion gene annotations.

42 ly on genome sequences, but also on inferred gene annotations.

43 en transcription and development and improve gene annotations.

44 orm comparative genomic analyses and improve gene annotations.

45 nal transcriptomic platforms with up-to-date gene annotations.

46 uilding phylogenies to predicting functional gene annotations.

47 n junctions with junctions in several recent gene annotations.

48 provements in sequence matching will improve gene annotations.

49 s, and created an additional 2,522 noncoding gene annotations.

50 transcriptomics to generate highly complete gene annotations.

51 a whole-community profile down to individual gene annotations.

52 to iteratively refine and improve structural gene annotations across multiple Aspergillus species, an

53 PIPETS is a statistically informed, gene-annotation agnostic methodology.

54 Functional gene annotation analysis indicated predominant effects o

55 n addition, ANISEED provides full functional gene annotation, anatomical ontologies and some gene exp

56 pped reads, balanced utilization of existing gene annotation and a reduced false discovery rate for s

57 accurate matching to reference sequences for gene annotation and allow in-depth analysis of sequence

58 ted, and combines the traditionally distinct gene annotation and alternative splicing detection proce

59 ble resource for knowledge representation in gene annotation and analysis in the areas of immunology

60 used in other genomics applications such as gene annotation and analysis of differential gene expres

61 ing pipelines produce consistent protein and gene annotation and capture sequence descriptors from se

62 nal annotation module that allows recovering gene annotation and detecting gene ontology enriched ter

63 expression datasets to perform comprehensive gene annotation and differential expression analysis.

64 (i) visualizing gene annotation and DNA sequence data from a GenBank fla

65 the 3' end of genes, which is important for gene annotation and elucidating gene regulation mechanis

66 ge patterns with genomic information such as gene annotation and evolutionary conservation.

67 The DIG system collects and organizes gene annotation and functional information, and includes

68 a need for accurate prediction of TFBSs for gene annotation and in applications such as evaluating t

69 Furthermore, in some cases, gene annotation and in aqua assays disagree by describin

70 analysis of genome structure and preliminary gene annotation and interpretation.

71 ctions of mitochondrial targeting sequences, gene annotation and links to phenotype and disease.

72 work has been focused on sequence assembly, gene annotation and metabolic network reconstruction.

73 m the fact that our current knowledge of the gene annotation and of the ontology structure is incompl

74 Gene annotation and pathway databases such as Gene Ontol

75 n protein structure and function prediction, gene annotation and phylogenetic tree construction.

76 GeneSense server was developed to integrate gene annotation and PPI networks in an expandable archit

77 In this release, the gene annotation and promoter sequences were expanded to

78 ch demonstrates broad utility for eukaryotic gene annotation and suggests an intriguing new decomposi

79 omics) designed to facilitate the process of gene annotation and the discovery of functional context.

80 sessment of the completeness and accuracy of gene annotation and thus allows computational identifica

81 dentification of splice sites is critical to gene annotation and to determine which sequences control

82 curacy in many applications, such as de novo gene annotation and transcript quantification.

83 At the gene level users can view the gene annotation and underlying evidence.

84 pecies include comprehensive, evidence-based gene annotations and a selected set of genomes includes

85 chin genome, associated expressed sequences, gene annotations and accessory resources.

86 These results greatly enhance sorghum gene annotations and aid in studying gene regulation in

87 nomic analysis and comparison, based on both gene annotations and associated metadata, with this init

88 e framework to quantify similarities between gene annotations and disease profiles.

89 imental datasets in consistency, recovery of gene annotations and enrichment for disease-associated v

90 ene predictions that do not overlap existing gene annotations and have developed a process for their

91 Functional protein association networks, gene annotations and localization of identified proteins

92 ERGR provides gene annotations and orthologs, detailed gene study info

93 lization of these occurrences with regard to gene annotations and other families of transposable elem

94 this capability has the potential to improve gene annotations and our understanding of the regulation

95 Over 10,000 gene annotations and phenotype descriptions from partici

96 des a user-friendly way to browse functional gene annotations and sequence comparisons with reference

97 algorithms that are not restricted by prior gene annotations and that account for alternative transc

98 In order to validate gene annotations and to identify pseudogenes that are po

99 ly interfaces hosting genomic resources with gene annotations and transcriptomic and proteomic data f

100 According to genes annotation and functional prediction, such as Wnt1

101 support customizable queries for all drugs, genes, annotations and associated data.

102 embly and gene model set, refined functional gene annotation, and anatomical ontologies, and a new co

103 e the last gene-rich gaps, improve duplicate gene annotation, and better understand copy-number-varia

104 scuss progress in Dictyostelium genomics and gene annotation, and highlight the primary portals for s

105 an independent measure of the efficiency of gene annotation, and indicates that this analysis may ac

106 rse MHC class II region with rigorous manual gene annotation, and it will serve as an important resou

107 functional enrichment, interactome analysis, gene annotation, and membership search to leverage over

108 Our model does not rely on existing gene annotations, and model selection is performed autom

109 ding genes and exons, spurious and incorrect gene annotations, and numerous unusual gene structures,

110 re information about the quality of microRNA gene annotations, and the cellular functions of their pr

111 rdinates, sequences (nucleotide/amino acid), gene annotations, and updated CDS information for microe

112 esigned to model the incompleteness of human gene annotations-and computed semantic similarities for

113 as dramatically improved contiguity, whereas gene annotations are available for just 34.3% of taxa.

114 However, often, existing gene annotations are erroneous, or only nucleotide seque

115 Databases collecting drug targets and gene annotations are growing and can be harnessed to she

116 down to examine specific matrix entries, and gene annotations are linked to relevant genomic database

117 Two zebrafish gene annotations are presented in Ensembl version 62 bui

118 Search mechanisms for the sequences and the gene annotations are provided.

119 and variable quality of evidence relevant to gene annotation argues for a probabilistic framework tha

120 of rapidly evolving genes, probably owing to gene annotation artifacts.

121 tations in the current sequence assembly and gene annotation, as well as approaches to address these

122 raw RNA-seq reads without prior knowledge of gene annotations, as well as for determining the dominan

123 es, expression analysis for microRNAs, basic gene annotation, batch analysis and linking between mous

124 e approach that reliably transfers essential gene annotations between distantly related bacteria.

125 quence similarity to improve the transfer of gene annotations between organisms.

126 Interestingly, semantic similarity between gene annotations (Biological Process) is much better ass

127 T utilizes a database that is preloaded with gene annotation, BLAST hit results, and gene-clustering

128 enic regions using Ensembl, UCSC and AceView gene annotations but they were not annotated into corres

129 Gene annotation by ab initio prediction supported by RNA

130 We improve gene annotation by generating more than two million full

131 The accuracy of gene annotation by this database was largely confirmed b

132 BAKIR aims to enhance the accuracy of KIR gene annotations by structuring its annotation pipeline

133 Errors in gene annotation can lead to errors in the quantification

134 Interacting PROTEINS: Furthermore, suitable gene annotations can also be captured.

135 ral schemes to predict an unambiguous set of genes (annotation CGG1), a set of reliable exons (annota

136 same genes, as indicated in a compendium of gene annotation data from numerous different sources.

137 SIM works well even for genomes with sparser gene annotation data.

138 ess (OA) subset of PubMed Central (PMC) as a gene annotation database and have developed an R package

139 roach can be easily generalized to any other gene annotation database.

140 Gene annotation databases (compendiums maintained by the

141 Several functional gene annotation databases have been developed in the rec

142 analysis of gene ontology from fly or human gene annotation databases points to four significant com

143 onal inference for non-coding elements using gene annotation databases requires a special correction.

144 ction that is used in many organism-specific gene annotation databases.

145 method and web-based tool, with 16 available gene annotation databases.

146 ine include the incorporation of genomes and gene annotation datasets for non-bovine ruminant species

147 Gene annotations, different transcript isoforms, nucleot

148 Current gene annotation efforts focus on centralized curation re

149 A gene annotation enrichment analysis using DAVID showed t

150 The gene-annotation enrichment analysis is a promising high-

151 One source of gene annotation error in eukaryotes arises from incorrec

152 e ongoing efforts to increase the quality of gene annotations, especially transcriptional start sites

153 evaluated the combination of cancer-related gene annotations, evolutionary conservation and pre-comp

154 Large-scale expression data, functional gene annotations, experimental protein-protein interacti

155 protocol for generating the H-MAGMA variant-gene annotation file by using chromatin interaction data

156 Lastly, we generated variant-gene annotation files for 28 tissues and cell types, wit

157 Our findings provide additional candidate-gene annotation for 37 disease susceptibility loci for h

158 s probably reflects the lesser refinement of gene annotation for chimpanzees.

159 GENCODE produces comprehensive reference gene annotation for human and mouse.

160 in all disjoint intervals of the Gencode V35 gene annotation for more than 19 000 GTExV8 BigWig files

161 To meet the needs of gene annotation for newly sequenced organisms, optimized

162 expression to tissue level, the accuracy of gene annotation for the nonspecific SAGE tags should be

163 ion tools and they have been widely used for gene annotation for various species.

164 We confirmed gene annotations for 384 120 genes, grouped 1 675 415 ge

165 We provide complete gene annotations for all supported species in addition t

166 users to automatically extract sequences and gene annotations for any recorded locus.

167 notation of contigs generated nearly 120,000 gene annotations for each species.

168 hes, including de novo genome assemblies and gene annotations for the population founders, have allow

169 It combines gene annotations from GenBank files and other sources wi

170 Gene annotation further revealed four genes with functio

171 This tool also allows users to overlay gene annotation, gene expression data and genome methyla

172 tools that enable flexible queries based on gene annotation, gene family, synteny and relative gene

173 By bringing together existing gene annotations, gene expression data, multiple-genome

174 phe necator and a high-quality mitochondrial gene annotation generated through cloning and Sanger seq

175 The zebrafish gene annotation has been enhanced by the incorporation o

176 Computational methods for structural gene annotation have propelled gene discovery but face c

177 nd automatically synthesizes these data into gene annotations having evidence-based quality indices.

178 based transcriptome profiling to structural gene annotation helped correct existing annotation error

179 le data consist of structural and functional gene annotations, homologous gene families, multiple seq

180 Our approach relies solely on gene annotation in a single reference genome, raw assemb

181 Gene annotation in eukaryotes is a non-trivial task that

182 nction that is used as a common language for gene annotation in many organisms.

183 ine addresses the critical need for accurate gene annotation in newly sequenced genomes, and we belie

184 catula, and the difficulties associated with gene annotation in plant secondary metabolism.

185 gain-of-function mutagenesis for functional gene annotation in vertebrate models, including zebrafis

186 Gene annotation in viruses often relies upon similarity

187 lows one to build an initial set of reliable gene annotations in potentially any eukaryotic genome, e

188 oach), for building a highly reliable set of gene annotations in the absence of experimental data.

189 In addition, there are 2380 gene annotations in the B73 genome that are located with

190 The Proteome Browser also provides links to gene annotations in the Genome Browser, the Known Genes

191 n Tetrahymena biology face challenges due to gene annotation inaccuracy, particularly the notable abs

192 ving to keep data up-to-date, new updates to gene annotations include GENCODE Genes, NCBI RefSeq Gene

193 re able to support or correct more than 6000 gene annotations including 80 novel gene structures and

194 mic and proteomic studies, as the quality of gene annotations incorporated into statistical analysis

195 ng with Noise set (DWCN), which makes use of gene annotation information and allows for a set of scat

196 he functional similarities of genes based on gene annotation information from heterogeneous data sour

197 r integrates and displays the mRNA and miRNA gene annotation information, signaling cascade pathways

198 Using currently available genome data and gene annotation information, we systematically examined

199 onjunction with BLAST searches and available gene annotation information.

200 ween human and mouse using only sequence and gene annotation information.

201 and comparative analyses based on reference gene annotations informs our understanding of gene funct

202 aught animals, using a combination of manual gene annotation, intact protein mass spectrometry and bo

203 ariable, candidate genes were identified and gene annotations investigated to demonstrate how this me

204 Gene annotation is a multi-label multi-class classificat

205 Comprehensive gene annotation is an essential aspect of genomic and pr

206 Prokaryote gene annotation is complicated by large numbers of short

207 RefSeq or user-provided gene annotation is displayed where available.

208 Since gene annotation is incomplete for even the best studied

209 Additionally, we show that unbiased gene annotation is key to accurately assessing R gene ev

210 ext based methods using gene names; however, gene annotation is neither complete, nor fully systemati

211 enome is sequenced and assembled, structural gene annotation is often the first step in analysis.

212 Gene annotation is the final goal of gene prediction alg

213 Gene annotation is the problem of mapping proteins to th

214 with four newly sequenced genomes (where the gene annotation is unavailable), we show that the gene p

215 ete and accurate set of human protein-coding gene annotations is perhaps the single most important re

216 four key areas: (1) transferring disease and gene annotation knowledge across species, (2) identifyin

217 es, ORFans are not attributable to errors in gene annotation, limitations of current databases, or to

218 cis-regulatory DNA sequences, most existing gene annotation methods, which exploit the conservation

219 of the human and mouse genomes and improved gene annotation methods.

220 general mass spectrometry-based approach for gene annotation of any organism and demonstrate its effe

221 Here we report the finished sequence and gene annotation of human chromosome 18, which will allow

222 We report a second-generation gene annotation of human chromosome 22.

223 Ab initio gene prediction enables gene annotation of new genomes regardless of availabilit

224 Gene annotation of significant SNPs identified candidate

225 Gene annotation of the identified proteins was corrected

226 We have generated an improved assembly and gene annotation of the pig X Chromosome, and a first dra

227 Here, we obtain comprehensive assembly and gene annotation of the sika deer (Cervus nippon) genome.

228 Here we present the genome and gene annotations of two such free-living Bradyrhizobium

229 ed on whole genome sequencing, sequences and genes annotation of the sheep (Ovis aries) Y chromosome

230 ineages share a large set of nonhousekeeping genes, annotation of lineage-restricted genes shows that

231 ing-array experiments agree with established gene annotation on human chromosome 22.

232 d and cost-effective way to provide reliable gene annotations on newly sequenced genomes.

233 crucial step in many analytic tasks such as gene annotation or expression studies.

234 ntropy within a selected region versus using gene annotation or known promoters as positives for tran

235 whole-genome assemblies without the need for gene annotation or markers.

236 We did gene annotation, pathway, and gene-set-enrichment analys

237 e a previously unexplored HAD family member (gene annotation, phosphoglycolate phosphatase), which we

238 and a previously proposed hybrid functional gene annotation pipeline, we developed an online pipelin

239 cordingly, fast and comprehensive functional gene annotation pipelines are needed to analyze and comp

240 expert manual gene annotators and automated gene annotation pipelines.

241 r plant biology related pathways, KEGG based gene annotation pointed out active presence of an array

242 BioGPS is a centralized gene-annotation portal that enables researchers to acces

243 l, variance stabilization, normalization and gene annotation portions.

244 Gene annotation predicted 25 428 protein-coding genes.

245 ng statistical power, or combine SNPs across gene annotations, preventing the discovery of allele spe

246 identification is an important aspect of the gene annotation process, requisite for the accurate deli

247 Despite advances in the gene annotation process, the functions of a large portio

248 Evigan is an automated gene annotation program for eukaryotic genomes, employin

249 Ensembl gene annotation provides a comprehensive catalog of tran

250 hat is independent of error-prone functional gene annotations remains a major open problem.

251 re is a crucial need to generate appropriate gene annotation repositories and resources.

252 en the abundance of new genomic projects and gene annotations, researchers trying to pinpoint causal

253 Many gene annotation resources and software platforms for ORA

254 dreds, possibly even thousands, of web-based gene annotation resources available, but it quickly beco

255 terature, gene transcriptional profiles, and gene annotation resources support our prediction.

256 ized gene portal for aggregating distributed gene annotation resources, emphasizing community extensi

257 at enables researchers to access distributed gene annotation resources.

258 evolutionary signatures to evaluate existing gene annotations, resulting in the validation of 87% of

259 to genome-wide RNA interference data and to gene annotations revealed distinguishable levels of expr

260 that the Open World Assumption as applied to gene annotations rules out many traditional validation m

261 ignment file, reference genome and reference gene annotation, ScanExitronLR outputs exitron events at

262 e sequence from which a core human reference gene annotation set can be derived.

263 experience gained in generating the GENCODE gene annotation set.

264 emblies, including bonobo and zebrafish; new gene annotation sets; improvements to track and assembly

265 However, conventional mRNA gene annotations significantly differ from the boundarie

266 Currently available gene annotation software applications depend on pre-cons

267 teins hampers their prediction with standard gene annotation software.

268 at functional proteomics complements current gene annotation strategies through the assessment of pro

269 Gene annotations, such as those in GENCODE, are derived

270 distribution appear to be due to artifactual gene annotation, suggesting the actual variation of prot

271 ve response, Cr1 We describe new markers and gene annotation that are both tightly linked to Cr1 in a

272 rsede the limited and static forms of single-gene annotation that are now the norm.

273 validated subset of genes from the reference gene annotation to characterize the structure, phylogeny

274 We took advantage of recent advances in gene annotation to develop the ags.sh and acn.sh tools t

275 ,686 were sufficiently distant from existing gene annotations to be considered a novel conserved unit

276 onal annotation tools by distilling multiple gene annotations to genome level summaries of functional

277 sortium has been producing reference quality gene annotations to provide this foundational resource.

278 suite of tools seamlessly integrates a novel gene annotation tool, known as GOby, which identifies st

279 Gene annotation underpins genome science.

280 In this study, we report fusion gene annotation updates aided by deep learning (FusionGD

281 This atlas greatly extends the gene annotation used in the original recount2 resource.

282 Here, we improved the Ae. arabicum gene annotation using 294 RNA-seq libraries and 136 307

283 sociated with detected sources of variation, gene annotation using publicly available databases and g

284 ) expanded support for genome sequence; (iv) gene annotation using the standardized vocabulary of Gen

285 Users can query the gene annotations using simple and powerful full text sea

286 Yet the quality of the assemblies and the gene annotations varies considerably and often remains p

287 patens were so far generated using different gene annotation versions and three different platforms:

288 ate gene expression queries across different gene annotation versions, and to access P. patens annota

289 Except for the latter, monocistronic gene annotation was expanded using the above criteria al

290 enome assembly was recently improved but the gene annotation was not updated.

291 e semantic similarities of GO terms used for gene annotation, we designed a new algorithm to measure

292 Analogous to the use of RNA-seq for gene annotation, we propose a new method for de novo TE

293 dicted based on their positions within known gene annotations, we find that 58.8% (923/1,570) of the

294 Taken together, with the most updated gene annotations, we reported a set of sQTL associated w

295 sufficient for full antimicrobial resistance gene annotation were obtained with as few as 2,000 to 5,

296 Gene annotations were curated in nine vertebrate model o

297 Gene annotations were updated using 111,000 full-length

298 nces, transcript fragmentation and incorrect gene annotation, which we suggest that de novo assembly

299 nd (ii) can assign structural and functional gene annotations with varying degrees of specificity to

300 on and in aqua assays disagree by describing gene annotation without enzyme activity and enzyme activ