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PROSITE is a protein database. It consists of entries describing the protein families, domains and functional sites as well as amino acid patterns and profiles in them. These are manually curated by a team of the Swiss Institute of Bioinformatics and tightly integrated into Swiss-Prot protein annotation. PROSITE was created in 1988 by Amos Bairoch, who…
Overview, Related Topics & Entities
Explore the main themes, entities and connections around PROSITE. Start with the topic map, then use the sections below for research and deeper semantic analysis.
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High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
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protein database analysis annotation sites patterns information swiss-prot functional amino functions known biologically expasy see swiss institute bioinformatics 1988 domain
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| PROSITE | Description | PROSITE, a protein domain database for functional characterization and annotation. | 1.00 | infobox |
| PROSITE | Laboratory | Structural Biology and Bioinformatics Department | 1.00 | infobox |
| PROSITE | Primary citation | .mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:r… | 1.00 | infobox |
| PROSITE | Release date | 1988 (1988) | 1.00 | infobox |
| PROSITE | Research center | Swiss Institute of Bioinformatics | 1.00 | infobox |
| PROSITE | Website | prosite.expasy.org | 1.00 | infobox |
| PROSITE | is a | protein database | 0.90 | text |
| PROSITE | related to External links | Official | 0.60 | section |
| PROSITE | see also | Uniprot | 0.60 | section |
| PROSITE | see also | InterPro | 0.60 | section |
| PROSITE | see also | Protein | 0.60 | section |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.