MOTIVATION: The number of protein records in the UniProt Knowledgebase (UniProtKB: https://www.uniprot.org) continues to grow rapidly as a result of genome sequencing and the prediction of protein-coding genes. Providing functional annotation for these proteins presents a significant and continuing challenge. RESULTS: In response to this challenge, UniProt has developed a method of annotation, known as UniRule, based on expertly curated rules, which integrates related systems (RuleBase, HAMAP, PIRSR, PIRNR) developed by the members of the UniProt consortium. UniRule uses protein family signatures from InterPro, combined with taxonomic and other constraints, to select sets of reviewed proteins which have common functional properties supported by experimental evidence. This annotation is propagated to unreviewed records in UniProtKB that meet the same selection criteria, most of which do not have (and are never likely to have) experimentally verified functional annotation. Release 2020_01 of UniProtKB contains 6496 UniRule rules which provide annotation for 53 million proteins, accounting for 30% of the 178 million records in UniProtKB. UniRule provides scalable enrichment of annotation in UniProtKB. AVAILABILITY AND IMPLEMENTATION: UniRule rules are integrated into UniProtKB and can be viewed at https://www.uniprot.org/unirule/. UniRule rules and the code required to run the rules, are publicly available for researchers who wish to annotate their own sequences. The implementation used to run the rules is known as UniFIRE and is available at https://gitlab.ebi.ac.uk/uniprot-public/unifire.

MOTIVATION: Similarity-based methods have been widely used in order to infer the properties of genes and gene products containing little or no experimental annotation. New approaches that overcome the limitations of methods that rely solely upon sequence similarity are attracting increased attention. One of these novel approaches is to use the organization of the structural domains in proteins. RESULTS: We propose a method for the automatic annotation of protein sequences in the UniProt Knowledgebase (UniProtKB) by comparing their domain architectures, classifying proteins based on the similarities and propagating functional annotation. The performance of this method was measured through a cross-validation analysis using the Gene Ontology (GO) annotation of a sub-set of UniProtKB/Swiss-Prot. The results demonstrate the effectiveness of this approach in detecting functional similarity with an average F-score: 0.85. We applied the method on nearly 55.3 million uncharacterized proteins in UniProtKB/TrEMBL resulted in 44 818 178 GO term predictions for 12 172 114 proteins. 22% of these predictions were for 2 812 016 previously non-annotated protein entries indicating the significance of the value added by this approach. AVAILABILITY AND IMPLEMENTATION: The results of the method are available at: ftp://ftp.ebi.ac.uk/pub/contrib/martin/DAAC/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups QuickGO has been a popular GO browser for many years, but after a recent redevelopment it is now able to offer a greater range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. AVAILABILITY AND IMPLEMENTATION: QuickGO has implemented in JavaScript, Ajax and HTML, with all major browsers supported. It can be queried online at http://www.ebi.ac.uk/QuickGO. The software for QuickGO is freely available under the Apache 2 licence and can be downloaded from http://www.ebi.ac.uk/QuickGO/installation.html

MOTIVATION: The advent of sequencing and structural genomics projects has provided a dramatic boost in the number of uncharacterized protein structures and sequences. Consequently, many computational tools have been developed to help elucidate protein function. However, such services are spread throughout the world, often with standalone web pages. Integration of these methods is needed and so far this has not been possible as there was no common vocabulary available that could be used as a standard language. RESULTS: The Protein Feature Ontology has been developed to provide a structured controlled vocabulary for features on a protein sequence or structure and comprises approximately 100 positional terms, now integrated into the Sequence Ontology (SO) and 40 non-positional terms which describe features relating to the whole-protein sequence. In addition, post-translational modifications are described by using a pre-existing ontology, the Protein Modification Ontology (MOD). This ontology is being used to integrate over 150 distinct annotations provided by the BioSapiens Network of Excellence, a consortium comprising 19 partner sites in Europe. AVAILABILITY: The Protein Feature Ontology can be browsed by accessing the ontology lookup service at the European Bioinformatics Institute (http://www.ebi.ac.uk/ontology-lookup/browse.do?ontName=BS).

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domain structure, post-translational modifications, variants, etc.), a minimal level of redundancy and a high level of integration with other databases. Together with its automatically annotated supplement TrEMBL, it provides a comprehensive and high-quality view of the current state of knowledge about proteins. Ongoing developments include the further improvement of functional and automatic annotation in the databases including evidence attribution with particular emphasis on the human, archaeal and bacterial proteomes and the provision of additional resources such as the International Protein Index (IPI) and XML format of SWISS-PROT and TrEMBL to the user community.

SUMMARY: One of the distinguishing criteria of the SWISS-PROT protein sequence data bank is minimal redundancy. The introduction of TrEMBL as a supplementary database ensured the comprehensiveness of SWISS-PROT and TrEMBL but introduced some degree of redundancy. We developed a strategy to identify the redundancy present within and between SWISS-PROT and TrEMBL and its subsequent removal. AVAILABILITY: The tools mentioned in this paper are available on request.