# UniProt: the Universal Protein Knowledgebase in 2023

Article · 

- Archive id: doi:10.1093/nar/gkac1052
- Published: 2023-01-01
- Venue: Nucleic acids research
- DOI: https://doi.org/10.1093/nar/gkac1052
- PMID: 36408920
- PMCID: PMC9825514
- Citations: 6,891
- Source URL: https://doi.org/10.1093/nar/gkac1052
- PDF: https://europepmc.org/articles/PMC9825514/pdf
- Provenance: europepmc

## Abstract

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication we describe enhancements made to our data processing pipeline and to our website to adapt to an ever-increasing information content. The number of sequences in UniProtKB has risen to over 227 million and we are working towards including a reference proteome for each taxonomic group. We continue to extract detailed annotations from the literature to update or create reviewed entries, while unreviewed entries are supplemented with annotations provided by automated systems using a variety of machine-learning techniques. In addition, the scientific community continues their contributions of publications and annotations to UniProt entries of their interest. Finally, we describe our new website (https://www.uniprot.org/), designed to enhance our users' experience and make our data easily accessible to the research community. This interface includes access to AlphaFold structures for more than 85% of all entries as well as improved visualisations for subcellular localisation of proteins.

_Abstract reproduced under CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)._

Topics: [AI Protein Design & Structure Prediction](https://space-kitty.com/topics/protein-design)

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