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1 in the EMBL Nucleotide Sequence Database and SWISS-PROT.
2 in the EMBL Nucleotide Sequence Database and SWISS-PROT.
3 diction using the language and the syntax of SWISS-PROT.
4 ow includes proteins from both SP-TrEMBL and SWISS-PROT.
5 structures covering 33% of all sequences in SWISS-PROT.
6 structures covering 36% of all sequences in Swiss-Prot.
7 in the EMBL Nucleotide Sequence Database and SWISS-PROT.
8 gy (GO) annotation of a sub-set of UniProtKB/Swiss-Prot.
9 n databases, which only include sequences in Swiss-Prot.
10 ch would facilitate text-mining of UniProtKB/Swiss-Prot.
11 487 CVD-related proteins was extracted from SWISS-PROT.
12 in the EMBL Nucleotide Sequence Database and SWISS-PROT.
13 ation for fewer than half of all proteins in SWISS-PROT.
14 ly diverse categories of human proteins from SWISS-PROT.
15 in the EMBL Nucleotide Sequence Database and SWISS-PROT.
16 in knowledge about the Keyword annotation in SWISS-PROT.
20 trinsic disorder in eukaryotic proteins from SWISS-PROT (47 +/- 4%) and in nonhomologous protein segm
23 is contained in databanks such as UniProtKB/Swiss-Prot and a manual analysis of these data allow FEP
24 tSubP on two independent data sets, one from Swiss-Prot and another containing green fluorescent prot
25 ding SGD, YPD and WormPD, Unigene, dbEST and SWISS-PROT and can be accessed at http://genome-www.stan
26 antify 11,352 gene products that span 70% of Swiss-Prot and capture protein regulation across the ful
30 The search engine allows one to search over SWISS-PROT and GenBank fields and then follow the links
34 ,747 proteins for which the manually curated Swiss-Prot and KEGG databases have agreeing Enzyme Commi
38 InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1,000,000 hits from 462
39 InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1000000 hits from 26433
41 ry database ensured the comprehensiveness of SWISS-PROT and TrEMBL but introduced some degree of redu
43 results have been calculated for the entire Swiss-Prot and TrEmbl database sequences (approximately
44 etely sequenced genomes (currently 154), the Swiss-Prot and TrEMBL databases and other sequence colle
45 varsplic.pl uses information present in the SWISS-PROT and TrEMBL databases to create new records fo
46 earch against the Homo sapiens subset of the SWISS-PROT and TrEMBL databases, we identified 68 protei
49 he UniProtKB, which contains only the latest Swiss-Prot and TrEMBL entry versions, the UniSave provid
50 tabase offers an automatic classification of SWISS-PROT and TrEMBL proteins into groups of related pr
52 NA sequences (EMBL-Bank), protein sequences (SWISS-PROT and TrEMBL), protein structure (MSD), whole g
55 erPro cover more than 74% of all proteins in SWISS-PROT and TrEMBL, an increase of nearly 15% since t
60 nd standardizing the annotation in the MIPS, Swiss-Prot and YPD databases, and we achieve 75 % accura
62 elated to cell death from HUGO, Ensembl, and SWISS-PROT, and about 700 Drosophila genes from FlyBase
63 uman gene databases, e.g. GDB, LocusLink and SWISS-PROT, and approved gene symbols are carefully co-o
64 ists of about 830 000 non-redundant PIR-PSD, SWISS-PROT, and TrEMBL proteins organized with more than
65 SCOP, full-length sequence information from Swiss-Prot, and verified functional information from the
70 re derived from the Protein Data Bank (PDB), Swiss-Prot, as well as Online Mendelian Inheritance in M
73 Biological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily s
76 on the variant phenotypic annotation of the Swiss-Prot database and focused our analysis on nsSNPs h
77 structed a dataset of protein sequences from SWISS-PROT database and segmented them into 12 classes b
78 ch as a complete genome or the non-redundant SWISS-PROT database can be processed in a few hours on a
79 ly 6 min on a single core PC to scan a whole Swiss-Prot database of approximately 540 000 sequences a
80 nformation retrieved from the well annotated SWISS-PROT database together with sequence information f
82 ustive classification of all proteins in the SWISS-PROT database, into groups of related proteins.
83 Integrated with the latest version of the Swiss-Prot database, the data provide precise correlatio
85 re retrieved from both PIR-International and SWISS-PROT databases, including a large number of new me
89 by the SWISS-PROT authors, we conclude that SWISS-PROT does not identify a significant number of exp
91 tically creates protein reports from sets of SWISS-PROT entries, collating results into structured re
93 polypeptide chain of rabbit uterine smMLCK (Swiss-Prot entry P29294) contains the catalytic/regulato
95 sequence identity with the OAH (An07g08390, Swiss-Prot entry Q2L887, 57% identity), we produced the
98 ng proteins (AfCS), eukaryotic proteins from SWISS-PROT (EU_SW) and non-homologous protein segments w
100 , including HGMD, OMIM, ClinVar, and UniProt/Swiss-Prot, followed by an overview of the computational
101 OSTA, and recommend changes to the UniProtKB/Swiss-Prot format, which would facilitate text-mining of
103 antly from the background of all residues in SWISS-PROT, from the group of surface residues, and from
104 two sections, corresponding to the familiar Swiss-Prot (fully manually curated entries) and TrEMBL (
105 onstrate that the vast majority of UniProtKB/Swiss-Prot functional annotations are of high quality, a
109 otein sequence with homologous proteins from SWISS-PROT; (iii) matching against human EST sequences.
113 inference through automatic text analysis of SWISS-PROT keywords (LOCkey) and de novo prediction thro
114 ons, stored in the database (EC identifiers, SWISS-PROT keywords and information from the Enzyme data
115 lly automated method for lexical analysis of SWISS-PROT keywords that assigns sub-cellular localizati
116 define domain folds and a thesaurus based on SWISS-PROT keywords to define functional categories.
117 alization through automatic text analysis of SWISS-PROT keywords; and (iv) LOC3Dini, ab initio predic
118 The TrEMBL database contains together with SWISS-PROT nearly all publicly available protein sequenc
123 One of the distinguishing criteria of the SWISS-PROT protein sequence data bank is minimal redunda
124 nces, Protein Information Resource (PIR) and SWISS-PROT protein sequence database feature table annot
125 The EBI also maintains and distributes the SWISS-PROT Protein Sequence database, in collaboration w
128 s of more than 200,000 non-redundant PIR and SWISS-PROT proteins organized with more than 28,000 supe
130 other data providers such as NCBI, RIKEN and SWISS-PROT provides standardization of gene:sequence ass
131 s found to be related based on LocusLink and SWISS-PROT references and sequence and taxonomy data.
134 comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniPr
136 genes do not exactly match the corresponding SWISS-PROT sequences, for reasons that include missing o
137 lL and R272P) was performed using the online Swiss-Prot server for automated modeling and analyzed an
139 rature and curated in collaboration with the Swiss-Prot team, making intensive use of controlled voca
140 roposed method on all SAPs obtained from the Swiss-Prot, the method achieves 0.42 MCC with 73.2% over
141 tomated analysis of annotations in UniProtKB/Swiss-Prot to enable groups of proteins already annotate
142 other databases (NCBI, Sanger Institute and SWISS-PROT) to provide standardization and interconnecti
143 er EBI databases including InterPro, GO, and SWISS-PROT, together with links to SCOP, CATH, PFAM and
144 information in EpoDB obtained from GenBank, SWISS-PROT, Transfac, TRRD and GERD is curated to provid
145 tabase offers an automatic classification of SWISS-PROT+TrEMBL proteins into groups of related protei
147 in sequences and functional information, the Swiss-Prot, TrEMBL and PIR protein database activities h
148 al annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized v
150 tated using BLAST search against the Aracyc, Swiss-Prot, TrEMBL, gene ontology and clusters of orthol
152 out 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with compos
153 ies from the following annotation databases: Swiss-Prot, TrEMBL, NREF, PIR, Gene Ontology, KEGG, Entr
155 utomated process, based on protein data from Swiss-Prot/TrEMBL (UniProt) and the associated mRNA data
156 through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a lo
157 126 unique protein sequences in the complete Swiss-Prot/TrEMBL database (August 25, 2003); only model
159 genome have identical sequence matches with SWISS-PROT/TrEMBL sequences, 13.4% have exact substring
160 es and easy links to the major protein (PDB, SWISS-PROT/TrEMBL, PIR-ALN, NCBI Taxonomy Browser) and l
162 ta relevant to red blood cells from GenBank, SWISS-PROT, TRRD (transcriptional regulation data) and G
163 he result of an iterative database search in SWISS-PROT using a position-weighted dynamic programming
165 ted as having the same function in UniProtKB/Swiss-Prot which can be used for large-scale analysis.
166 sers can reliably identify those proteins in SWISS-PROT whose functions were determined experimentall
167 NPs in dbSNP and amino acid substitutions in Swiss-Prot with protein structural information, if avail
168 NPs in dbSNP and amino acid substitutions in Swiss-Prot with protein structural information, links to
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