ライフサイエンスコーパス: protein database

1 11% of BESs have homology to the Arabidopsis protein database.

2 m other species in the GenBank NR nucleotide/protein database.

3 18 chitinase-like proteins in the Drosophila protein database.

4 sts of true positives from the non-redundant protein database.

5 lyzed, 46 were identified by matching to the protein database.

6 when run against the complete non-redundant protein database.

7 A with motif databases and the non-redundant protein database.

8 erformed by searching an Internet-accessible protein database.

9 y digested peptides derived from a reference protein database.

10 pha-actinin sequences deposited in the Swiss Protein Database.

11 ching top-down tandem mass spectra against a protein database.

12 for unique retrieval of this enzyme from the protein database.

13 oil based on the phi, psi distributions in a protein database.

14 tics pipeline with a comprehensive hazardous protein database.

15 d by searches of the data against an E. coli protein database.

16 eads need to be mapped directly to a gene or protein database.

17 on-isobaric mutations for every residue in a protein database.

18 ct from the members available in the current protein database.

19 st in silico produced spectra derived from a protein database.

20 s with different levels of representation in protein databases.

21 at incorporates structural bias derived from protein databases.

22 similarity to any other sequences present in protein databases.

23 on through homology searches at nonredundant protein databases.

24 compared with conventional searches against protein databases.

25 s and sequencing errors have propagated into protein databases.

26 xample, annotation of microarray data and of protein databases.

27 provide links to PubMed abstracts and major protein databases.

28 build motifs that could be searched against protein databases.

29 on the basis of blastX searches against all protein databases.

30 identification using tandem mass spectra and protein databases.

31 ction of CIN85 novel-interacting partners in protein databases.

32 tly present in the widely used nr and TrEMBL protein databases.

33 ence of p300 have been identified in current protein databases.

34 notated and classified functionally based on protein databases.

35 and searched against on-line nucleotide and protein databases.

36 ags that do not match entries in the DNA and protein databases.

37 ), PO4(3-)) that are most frequently seen in protein databases.

38 and ORF3 were found in the nucleic acid and protein databases.

39 significant similarity to members of DNA or protein databases.

40 s of similarity searches with nucleotide and protein databases.

41 with sequences in the NCBI nucleic acid and protein databases.

42 optimization of representative sequences in protein databases.

43 roduction of new genomes and quickly growing protein databases.

44 protein structure by leveraging the relevant protein databases.

45 ching of the spectral data against bacterial protein databases.

46 s relies heavily on the presence of complete protein databases.

47 o acid sequences are unlike any published in protein databases.

48 r and compilation of information from online protein databases.

49 s, as well as external links to sequence and protein databases.

50 cted by covariance analyses of two-component protein databases.

51 Republished from Current BioData's Targeted Proteins database.

52 erived from the structural classification of proteins database.

53 uccessor to the Structural Classification of Proteins database.

54 We analyzed structural data of a membrane proteins database.

55 oto Encyclopedia of Genes and Genomes (KEGG) protein database; 2) a web viewing application that disp

56 Based on an annotated human cardiac protein database, 62% have at least one PTM (phosphoryla

57 abase retrieval algorithm (Retriever), MySQL protein databases, a file/data manager, and a project tr

58 ogies and increasing size of both genome and protein databases, a need for faster Smith-Waterman impl

59 tricted coding sequences not found in public protein databases, a web-based WU-BLAST search tool that

60 ts of the SCOP (Structural Classification of Proteins) database, a gold standard for protein structur

61 information, the Swiss-Prot, TrEMBL and PIR protein database activities have united to form the Univ

62 nslated DNA sequence to each sequence in the protein database, allowing gaps and frameshifts.

63 es using both short-read RNA-seq and a large protein database, along with statistical models learned

64 Protein database analyses of the peptides, CVSNPRWKC and

65 Membrane protein database analyses suggest even weaker affinity f

66 as identified by peptide microsequencing and protein database analysis as troponin I (TnI).

67 ionization mass spectrometry (MALDI-MS) and protein database analysis.

68 extra genes in both GenBank's non-redundant protein database and all of the metagenomes in the seque

69 With a newly designed index structure for protein database and associated optimizations in BLASTP

70 In parallel to milk protein database and de novo searches, the retention tim

71 y maintaining a comprehensive, non-redundant protein database and for creating a quarterly release of

72 Protein database and pathway/network analytical software

73 against a plant transcript database, the NR protein database and six newly-sequenced genomes (Carica

74 iver biopsy protein digest using the Huh-7.5 protein database and the accurate mass and time tag stra

75 one for comparing the query sequence with a protein database and the other for comparing the query w

76 sequence-structure motifs as observed in the protein database and, by representing overlapping motifs

77 , 78% had similarity matches to sequences in protein databases and 83% had exact expressed sequence t

78 asets from this study can be readily used as protein databases and as such serve as basis for further

79 Bank nucleotides patent class and the patent protein databases and contain value-added annotations fr

80 k all peptides in public viral and bacterial protein databases and identify potential molecular mimic

81 We describe how to use public protein databases and molecular modeling programs to sel

82 that combines results from several reference protein databases and returns the matching annotations t

83 The widening function annotation gap in protein databases and the increasing number and diversit

84 ndem mass spectra to peptides derived from a protein database, and (2) mapping assigned peptides to p

85 A queries, (2) available for searches of any protein database, and (3) more up-to-date, with periodic

86 ected from the same protein mixture, a FASTA protein database, and a selection of possible PTMs, the

87 ted with BLASTx using the non-redundant (nr) protein database, and Gene Ontology (GO) terms were assi

88 m all organisms in the GenBank non-redundant protein database, and the HMMs have been used to classif

89 ed to the NCBI Taxonomy database, the Entrez Protein database, and the scientific literature in PubMe

90 75 are tentatively assigned to proteins in a protein database, and these proteins are characterized b

91 determined structural information in folded protein databases, and disorder predictors rely on sever

92 d methods for data mining of the literature, protein databases, and knowledge bases (IT.Omics LSGraph

93 were obtained through SEQUEST searches of a protein database appended with its decoy (reversed seque

94 otechnology Information (NCBI) non-redundant protein database approaches 90%.

95 A searchable protein database, ARABI-COIL, was established that integ

96 l packings and topologies with no analogs in protein database are identified.

97 However, because the EST and protein databases are constantly growing, in many cases

98 PrecisionProDB and pre-calculated protein databases are freely available at and

99 roteomic analyses of higher eukaryotes where protein databases are large.

100 ustering speed is needed because the size of protein databases are rapidly growing and many applicati

101 initions in the Structural Classification of Proteins Database are used, so that we can view all pair

102 esults, and pre-computed links from Entrez's protein database, are calculated using the RPS-BLAST alg

103 r for Biotechnology Information nonredundant protein database as likely parallel beta-helices.

104 integrates and links the main nucleotide and protein databases as well as many other specialist molec

105 no acids, leads to spurious matches in large protein databases, as indicated by high BLAST Expect val

106 we have constructed an Alternatively Spliced Proteins database (ASP) from analysis of human expressed

107 Protein entries in databases such as Entrez Protein database at NCBI contain information about publi

108 P5 was not homologous to any sequence in the protein database at the National Center for Biotechnolog

109 st and flexible program for clustering large protein databases at different sequence identity levels.

110 library peptides to probe the non-redundant protein database, bacterial peptides that elicited funct

111 forms similarity searches of the NCBI Entrez Protein Database based on domain architecture, defined a

112 MS platforms and construction of customized protein databases based on RNA-Seq data with or without

113 y when searching MS/MS spectra against large protein databases because of their atypical lengths (e.g

114 which scale linearly in the size of the full protein database being searched.

115 Binary subcomplexes in proteins database (BISC) is a new protein-protein intera

116 andem mass spectrometry requires a reference protein database, but these are only available for model

117 h those derived theoretically from the Swiss Protein Database by computer-based comparisons.

118 With the proposed approach, a protein database can be preprocessed and stored for late

119 or ambiguities in the NCBI nucleic acid and protein databases can also cause errors in BLAST-based t

120 hich does not have any known homologs in the protein databases, causes cells to form biofilms that ar

121 The non-redundant protein database constructed from the proteins encoded b

122 A high-quality liver protein database containing 5,920 unique protein identif

123 rotein Sequence Database (PSD), an annotated protein database containing over 283 000 sequences cover

124 To test this hypothesis, we analyzed protein databases containing subsets of proteins that ar

125 Rapidly growing protein databases demand faster sensitive search tools.

126 e brain vasculome with representative plasma protein databases demonstrated significant overlap, sugg

127 g novel peptides by searching the customized protein database derived from RNA-Seq data.

128 enging due to the size and incompleteness of protein databases derived from metagenomes.

129 r previous study showed that sample-specific protein databases derived from RNA-Seq data can better a

130 Optimization of sample preparations and protein database developments are enhancing the quantity

131 A search of protein databases disclosed that the P47 peptide mass pr

132 length, e-value threshold, and the choice of protein database dramatically impact detection of a know

133 rary size selection, read length and format, protein database, e-value threshold, and sequencing dept

134 cient for matching nanospectra against small protein databases, e.g., protein identification in bacte

135 ein count is not inflated by variants in the protein database, eliminating approximately 25% of redun

136 all SWISS-PROT, TrEMBL, Genpept and Ensembl protein database entries are now possible with run times

137 juvenile Fugu tissues, 74% of which matched protein database entries.

138 By screening the public protein database for Atg32 homologues, we identify Bcl2-

139 re used in this study, including the UniProt protein database for crop physiochemical properties asso

140 spectrometry are searched directly against a protein database for identification of the protein from

141 sequencing of expressed mRNA can generate a protein database for mass spectrometry-based identificat

142 provides the first comprehensive echinoderm protein database for neural tissue, including numerous s

143 PHI-BLAST searches a protein database for other instances of the input patter

144 sequence information can be used to search a protein database for protein identification.

145 t is specialized for generating a personized protein database for proteomics applications.

146 d its analogues to define motifs to search a protein database for structural homologues of PLP139-151

147 ng an automatic SEQUEST search of the single protein database for this antibody and extensive manual

148 We established criteria for searching protein databases for prion candidates and found several

149 Man (OMIM) human genetics database and other protein databases for the selection of attractive target

150 searching LC-MS/MS data against a customized protein database from RNA-Seq may produce a subset of al

151 a from NCBI's SNP database (dbSNP), gene and protein databases from Entrez, protein structures from t

152 STX search with all tags of the nonredundant protein database gave only 161 unique significant matche

153 mass spectra are often searched against huge protein databases generated from genomes or RNA-Seq data

154 The availability of large protein databases generated from sequences of hundreds o

155 The recent growth in protein databases has revealed the functional diversity

156 illion protein sequences in the nonredundant protein database have no structural information, it is d

157 ently in use for querying MS/MS data against protein databases have been optimized on the basis of ma

158 unction relationships is presented: the Heme Protein Database (HPD).

159 quence similarity searches of nucleotide and protein databases identified the first homologs of MAGP1

160 and other known invasion genes when DNA and protein databases in GenBank were searched.

161 New protein databases include structure predictions for huma

162 ries increases linearly as the volume of the protein databases increase.

163 g the Virus Orthologous Groups and ViralZone protein databases indicated that the novel soft alignmen

164 rom the NCBI RefSeq nonredundant and UniProt protein databases into 35 canonical and seven pseudokina

165 rs and that the best structural match in the protein database is to the variable lymphocyte receptor

166 The UniProt Reference Clusters (UniRef100) protein database is used as the reference database for t

167 programs in proteomics, a standard reference protein database is used.

168 Comparing two protein databases is a fundamental task in biosequence a

169 matching tandem mass spectra (MS/MS) against protein databases is a widespread tool in mass spectrome

170 dress this deficit, functional annotation in protein databases is often inferred by sequence similari

171 The SCOP (Structural Classification of Proteins) database is a comprehensive ordering of all pr

172 novel peptide detection with the customized protein database, is necessary.

173 Because AidA has no homologs in the protein databases, its discovery provided no clues as to

174 Clustering large protein databases like the NCBI Non-Redundant database (

175 This database, the Ligand-Protein DataBase (LPDB), is designed to allow the select

176 Leveraging accumulative protein databases, machine learning (ML) models, particu

177 Moreover, in general protein databases, many families already classified as p

178 junctions identified from RNA-Seq data make protein database more complete and sample-specific.

179 equences of these unigenes against different protein databases, nearly 60% of them were annotated and

180 In contrast, RNA expression and protein databases need to be able to handle very high di

181 The Nuclear Protein Database (NPD) is a curated database that contai

182 ecific databases, the beta-lactam-resistance protein database of A. baumannii (BRPDAB).

183 mparison and clustering of the non-redundant protein database of over 560,000 sequences on a high-end

184 he CluSTr (Clusters of SWISS-PROT and TrEMBL proteins) database offers an automatic classification of

185 A customized protein database on the basis of RNA-Seq data is thus pr

186 formance by adopting the more representative protein database or adding population and individual-spe

187 we have introduced a non-redundant reference protein database, PIR-NREF.

188 integrates and links the main nucleotide and protein databases plus many other specialized databases.

189 integrates and links the main nucleotide and protein databases plus many other specialized molecular

190 egrating and linking the main nucleotide and protein databases plus many specialised databases.

191 integrates and links the main nucleotide and protein databases plus many specialized databases.

192 egrating and linking the main nucleotide and protein databases, plus many specialised databases.

193 ein products of which have clear homologs in protein databases, predictions were recomputed by Fgenes

194 The Arabidopsis Nucleolar Protein Database provides information on 217 proteins id

195 teins (which make up >65% of the large-scale protein databases) provides a valuable tool for function

196 miRNAs were also elucidated from the EST and protein databases, providing additional evidence for the

197 ng a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering,

198 Using public nucleotide and protein databases, reads were aligned for pathogen ident

199 Therefore, the protein database required for the interpretation of spec

200 of DNA reads from such samples to reference protein databases requires long run-times, and short rea

201 BLASTP searches of the NCBI protein database revealed clear homologies in three pept

202 first 20 amino acid residues of Tpn with the protein databases revealed a high degree of homology to

203 Comparisons with protein databases revealed homologies to (a) ubiquitin,

204 A search of the protein databases revealed sequence similarities to O-me

205 he GSSs with sequences in the public DNA and protein databases revealed that 107 contigs (26%) displa

206 Comparison of Tnk1 to available sequences in protein databases reveals that it is most homologous to

207 definitions in Structural Classification of Proteins Database (SCOP) in order to map pairs of adjace

208 rmat or enter a Structural Classification of Proteins database (SCOP)/PDB identifier for which NCI id

209 tes the need for specific parametrization of protein database search algorithms.

210 Through comprehensive protein database search and phylogenetic analysis, the T

211 We present a protein database search engine for the automatic identif

212 To test this idea, a protein database search for potential MART-1 epitope mim

213 demonstrated potential to supplant classical protein database search methods based on sequence alignm

214 The protein database search or the spectral library search a

215 The PSI-BLAST protein database search program derives the column score

216 A version of the BLAST protein database search program, modified to employ this

217 ggest possible improvements to the PSI-BLAST protein database search program.

218 A protein database search revealed that AlgZ is homologous

219 m for restriction to certain autoantigens, a protein database search was done for homologies with seq

220 For protein database search, it identifies 6%-15% more uniqu

221 ypeptides from C. elegans and S. pombe, in a protein database search.

222 Protein database searches demonstrate Tdd-4 encoded prot

223 approach that combines spectral library and protein database searches for peptide identification.

224 been designed and implemented such that most protein database searches return within a few seconds.

225 man, mouse, rat and Drosophila muskelins and protein database searches revealed a novel highly conser

226 DNA and protein database searches revealed that SEND32, SEND35,

227 Protein database searches revealed that SusE had limited

228 web-based email alert system for monitoring protein database searches using HMMER and Blast-P, nucle

229 Protein database searches using the consensus PDZ-bindin

230 Protein database searches were performed using the masse

231 Protein identification is carried out using protein database searches with search scoring systems, w

232 ope sequence data so as to enable successful protein database searches.

233 loss of information compared to conventional protein database searches.

234 ion of domain and functional predictions for protein database searches.

235 Protein database searching and molecular modeling reveal

236 An example of the use of protein database searching of a partial peptide sequence

237 -generated partial sequence information with protein database searching techniques are presented.

238 Using this motif as a protein database searching tool, we find that it is pres

239 -desorption ionization mass spectrometry and protein database searching, the 40-kilodalton ligand was

240 ied by mass spectrometry in combination with protein database searching.

241 The sequences obtained are used for protein database searching.

242 ected tandem mass spectrometry combined with protein database searching.

243 ntial residues for channel functions in Orai proteins, database searching also identifies a putative

244 le the data and interrogate the nonredundant protein database, searching for a close match.

245 The protein database section features important updates on t

246 As of November 23rd 2020, the NCBI protein database showed 11,227 proteins from A. alternat

247 An alignment of 67 SLN sequences from the protein databases shows that 19 of them contain a cystei

248 further curated several ruminant eukaryotic protein databases, significantly enhancing our ability t

249 acid databases and in all six frames to the protein databases: Sixeen clones could be assigned to kn

250 th the following novel features: (1) a novel protein database structure containing extensive preindex

251 ted OBPs using multi-sequence alignment with protein database structures.

252 peptide sequences are aligned to an internal protein database such as UniProtKB.

253 Analysis of protein databases suggests most eukaryotic genomes encod

254 oteomic database searching with a customized protein database that incorporates sample- or disease-sp

255 vel problem can lead to errors in genome and protein databases that are often not recognized or ackno

256 technology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Labora

257 the residue probability distributions in the protein database; the decoupling of the distance and env

258 and hood have no structural precedent in the protein database, therefore representing new folds.

259 r for Biotechnology Information nonredundant protein database to determine the phylogenetic relatedne

260 Most of these computer programs use a protein database to match peptide sequences to the obser

261 the millions of decapeptides contained in a protein database to rank and predict the most stimulator

262 age processing, and are pre-trained on large protein databases to generate contextualized representat

263 es sequence similarity search against custom protein databases to identify protein coding regions, st

264 g BLAST similarity comparisons to the public protein databases to identify putative genes.

265 ch, was applied to >13,000 such domains from protein databases to identify residue contacts between t

266 ent mass spectrometry (MS/MS), and searching protein databases to identify the proteins from which th

267 r proteins, using predictive analysis from a protein database, to see whether this may be related to

268 A search of the protein databases uncovered many additional putative pho

269 protein that is not present in an annotated protein database using a "top-down" approach with a quad

270 ived from the MS/MS data was compared with a protein database using BLAST software, revealing homolog

271 proximately 280000 entries in a nonredundant protein database using SEQUEST.

272 BLAST searches of the NCBInr protein database using the amino acid sequence of MiSp1-

273 Markov model profile-to-profile searches in protein databases using endoplasmic reticulum lumen prot

274 Bayesian algorithm to identify proteins from protein databases using mass spectrometric peptide mappi

275 important for those applications that search protein databases using the de novo sequencing results.

276 programs that primarily interact with large protein databases via precisely these tools.

277 A macaque protein database was assembled and used in the identific

278 ss to analyze sequences in the Non-redundant Protein Database, we compared predicted BMC loci found i

279 orating cell line-specific variants into the protein database, we demonstrated a 0.71% improvement fo

280 imilar amino acid sequences retrievable from protein databases, we have identified the following moti

281 Tool for the Retrieval of Interacting Genes/Proteins) databases, we unravelled the intricate network

282 similarities to viruses in the nonredundant protein database were selected.

283 rimental data can be used interactively with protein databases when the modified protein of interest

284 ication programs are restricted to searching protein databases where data are often lagging behind th

285 ation for sequences tracked in NCBI's Entrez protein database, which can be retrieved for single sequ

286 a are not present in most publicly available protein databases, which only include sequences in Swiss

287 positives, finding that BLAST against NCBI's protein database will now incorrectly categorize a numbe

288 zinc metalloproteases can be founded in the protein database with a cysteine at a similar location,

289 This program can efficiently cluster a huge protein database with millions of sequences.

290 Combining the secretory protein database with RNA-sequencing and quantitative PC

291 t as advances in sequencing technology flood protein databases with an exponentially growing number o

292 Searches of the major public protein databases with core and linker chicken and human

293 enerated human population-specific reference protein databases with PrecisionProDB, which improves th

294 tigen can be rapidly identified by searching protein databases with the mass spectral data in conjunc

295 The Yeast Protein Database (YPD) is a curated database for the pro

296 The Yeast Protein Database (YPD) is a database for the proteins of