InterPro: the protein sequence classification resource in 2025 Article Swipe
Matthias Blum
,
Antonina Andreeva
,
Laise Cavalcanti Florentino
,
Sara Chuguransky
,
Tiago Grego
,
Emma Hobbs
,
Beatriz Lázaro
,
A. Orr
,
Typhaine Paysan‐Lafosse
,
Irina Ponamareva
,
Gustavo A Salazar
,
Nicola Bordin
,
Peer Bork
,
Alan Bridge
,
Lucy J. Colwell
,
Julian Gough
,
Daniel H. Haft
,
Ivica Letunić
,
Felipe Llinares-López
,
Aron Marchler‐Bauer
,
Laetitia Meng-Papaxanthos
,
Huaiyu Mi
,
Darren A. Natale
,
Christine Orengo
,
Arun Prasad Pandurangan
,
Damiano Piovesan
,
Catherine Rivoire
,
Christian J A Sigrist
,
Narmada Thanki
,
Françoise Thibaud‐Nissen
,
Paul D. Thomas
,
Silvio C. E. Tosatto
,
Cathy Wu
,
Alex Bateman
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/nar/gkae1082
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/nar/gkae1082
InterPro (https://www.ebi.ac.uk/interpro) is a freely accessible resource for the classification of protein sequences into families. It integrates predictive models, known as signatures, from multiple member databases to classify sequences into families and predict the presence of domains and significant sites. The InterPro database provides annotations for over 200 million sequences, ensuring extensive coverage of UniProtKB, the standard repository of protein sequences, and includes mappings to several other major resources, such as Gene Ontology (GO), Protein Data Bank in Europe (PDBe) and the AlphaFold Protein Structure Database. In this publication, we report on the status of InterPro (version 101.0), detailing new developments in the database, associated web interface and software. Notable updates include the increased integration of structures predicted by AlphaFold and the enhanced description of protein families using artificial intelligence. Over the past two years, more than 5000 new InterPro entries have been created. The InterPro website now offers access to 85 000 protein families and domains from its member databases and serves as a long-term archive for retired databases. InterPro data, software and tools are freely available.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/nar/gkae1082
- https://academic.oup.com/nar/advance-article-pdf/doi/10.1093/nar/gkae1082/60766178/gkae1082.pdf
- OA Status
- gold
- Cited By
- 463
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404531735
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4404531735Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/nar/gkae1082Digital Object Identifier
- Title
-
InterPro: the protein sequence classification resource in 2025Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-20Full publication date if available
- Authors
-
Matthias Blum, Antonina Andreeva, Laise Cavalcanti Florentino, Sara Chuguransky, Tiago Grego, Emma Hobbs, Beatriz Lázaro, A. Orr, Typhaine Paysan‐Lafosse, Irina Ponamareva, Gustavo A Salazar, Nicola Bordin, Peer Bork, Alan Bridge, Lucy J. Colwell, Julian Gough, Daniel H. Haft, Ivica Letunić, Felipe Llinares-López, Aron Marchler‐Bauer, Laetitia Meng-Papaxanthos, Huaiyu Mi, Darren A. Natale, Christine Orengo, Arun Prasad Pandurangan, Damiano Piovesan, Catherine Rivoire, Christian J A Sigrist, Narmada Thanki, Françoise Thibaud‐Nissen, Paul D. Thomas, Silvio C. E. Tosatto, Cathy Wu, Alex BatemanList of authors in order
- Landing page
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https://doi.org/10.1093/nar/gkae1082Publisher landing page
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https://academic.oup.com/nar/advance-article-pdf/doi/10.1093/nar/gkae1082/60766178/gkae1082.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://academic.oup.com/nar/advance-article-pdf/doi/10.1093/nar/gkae1082/60766178/gkae1082.pdfDirect OA link when available
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UniProt, Biology, Database, Bioinformatics, Computational biology, Computer science, Genetics, GeneTop concepts (fields/topics) attached by OpenAlex
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463Total citation count in OpenAlex
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2025: 449, 2024: 13, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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58Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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