Chapter title |
UniProtKB/Swiss-Prot.
|
---|---|
Chapter number | 4 |
Book title |
Plant Bioinformatics
|
Published in |
Methods in molecular biology, February 2008
|
DOI | 10.1007/978-1-59745-535-0_4 |
Pubmed ID | |
Book ISBNs |
978-1-58829-653-5, 978-1-59745-535-0
|
Authors |
Emmanuel Boutet, Damien Lieberherr, Michael Tognolli, Michel Schneider, Amos Bairoch, Boutet, Emmanuel, Lieberherr, Damien, Tognolli, Michael, Schneider, Michel, Bairoch, Amos |
Abstract |
The Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI), and the Protein Information Resource (PIR) form the Universal Protein Resource (UniProt) consortium. Its main goal is to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB) and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc). (1) UniProtKB is a comprehensive protein sequence knowledgebase that consists of two sections: UniProtKB/Swiss-Prot, which contains manually annotated entries, and UniProtKB/TrEMBL, which contains computer-annotated entries. UniProtKB/Swiss-Prot entries contain information curated by biologists and provide users with cross-links to about 100 external databases and with access to additional information or tools. (2) The UniRef databases (UniRef100, UniRef90, and UniRef50) define clusters of protein sequences that share 100, 90, or 50% identity. (3) The UniParc database stores and maps all publicly available protein sequence data, including obsolete data excluded from UniProtKB. The UniProt databases can be accessed online (http://www.uniprot.org/) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every 2 weeks. The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry, paying particular attention to the specificities of plant protein annotation. We will also present some of the tools and databases that are linked to each entry. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 2 | <1% |
Brazil | 2 | <1% |
United Kingdom | 2 | <1% |
Spain | 2 | <1% |
United States | 2 | <1% |
Unknown | 281 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 69 | 24% |
Student > Master | 48 | 16% |
Researcher | 41 | 14% |
Student > Bachelor | 24 | 8% |
Student > Doctoral Student | 15 | 5% |
Other | 37 | 13% |
Unknown | 57 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 97 | 33% |
Biochemistry, Genetics and Molecular Biology | 75 | 26% |
Computer Science | 11 | 4% |
Chemistry | 8 | 3% |
Pharmacology, Toxicology and Pharmaceutical Science | 5 | 2% |
Other | 28 | 10% |
Unknown | 67 | 23% |