| URL: | http://pairsdb.csc.fi/ |
| Full name: | Pairs Database |
| Description: | PairsDB is a database intended to make exploring protein sequences and their similarity relationships quick and easy. |
| Year founded: | 2008 |
| Last update: | 2008-01-01 |
| Version: | |
| Accessibility: |
Unaccessible
|
| Country/Region: | United Kingdom |
| Data type: | |
| Data object: |
NA
|
| Database category: | |
| Major species: |
NA
|
| Keywords: |
| University/Institution: | University of Oxford |
| Address: | UK |
| City: | Oxford |
| Province/State: | Oxfordshire |
| Country/Region: | United Kingdom |
| Contact name (PI/Team): | Liisa Holm |
| Contact email (PI/Helpdesk): | liisa.holm@helsinki.fi |
|
PairsDB atlas of protein sequence space. [PMID: 17986464]
Sequence similarity/database searching is a cornerstone of molecular biology. PairsDB is a database intended to make exploring protein sequences and their similarity relationships quick and easy. Behind PairsDB is a comprehensive collection of protein sequences and BLAST and PSI-BLAST alignments between them. Instead of running BLAST or PSI-BLAST individually on each request, results are retrieved instantaneously from a database of pre-computed alignments. Filtering options allow you to find a set of sequences satisfying a set of criteria-for example, all human proteins with solved structure and without transmembrane segments. PairsDB is continually updated and covers all sequences in Uniprot. The data is stored in a MySQL relational database. Data files will be made available for download at ftp://nic.funet.fi/pub/sci/molbio. PairsDB can also be accessed interactively at http://pairsdb.csc.fi. PairsDB data is a valuable platform to build various downstream automated analysis pipelines. For example, the graph of all-against-all similarity relationships is the starting point for clustering protein families, delineating domains, improving alignment accuracy by consistency measures, and defining orthologous genes. Moreover, query-anchored stacked sequence alignments, profiles and consensus sequences are useful in studies of sequence conservation patterns for clues about possible functional sites. |