MOTIVATION: To provide high quality, computationally tractable annotation of binding sites for biologically relevant (cognate) ligands in UniProtKB using the chemical ontology ChEBI (Chemical Entities of Biological Interest), to better support efforts to study and predict functionally relevant interactions between protein sequences and structures and small molecule ligands. RESULTS: We structured the data model for cognate ligand binding site annotations in UniProtKB and performed a complete reannotation of all cognate ligand binding sites using stable unique identifiers from ChEBI, which we now use as the reference vocabulary for all such annotations. We developed improved search and query facilities for cognate ligands in the UniProt website, REST API and SPARQL endpoint that leverage the chemical structure data, nomenclature and classification that ChEBI provides. AVAILABILITY AND IMPLEMENTATION: Binding site annotations for cognate ligands described using ChEBI are available for UniProtKB protein sequence records in several formats (text, XML and RDF) and are freely available to query and download through the UniProt website (www.uniprot.org), REST API (www.uniprot.org/help/api), SPARQL endpoint (sparql.uniprot.org/) and FTP site (https://ftp.uniprot.org/pub/databases/uniprot/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:[email protected].

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: To provide high quality computationally tractable enzyme annotation in UniProtKB using Rhea, a comprehensive expert-curated knowledgebase of biochemical reactions which describes reaction participants using the ChEBI (Chemical Entities of Biological Interest) ontology. RESULTS: We replaced existing textual descriptions of biochemical reactions in UniProtKB with their equivalents from Rhea, which is now the standard for annotation of enzymatic reactions in UniProtKB. We developed improved search and query facilities for the UniProt website, REST API and SPARQL endpoint that leverage the chemical structure data, nomenclature and classification that Rhea and ChEBI provide. AVAILABILITY AND IMPLEMENTATION: UniProtKB at https://www.uniprot.org; UniProt REST API at https://www.uniprot.org/help/api; UniProt SPARQL endpoint at https://sparql.uniprot.org/; Rhea at https://www.rhea-db.org.

MOTIVATION: On the semantic web, in life sciences in particular, data is often distributed via multiple resources. Each of these sources is likely to use their own International Resource Identifier for conceptually the same resource or database record. The lack of correspondence between identifiers introduces a barrier when executing federated SPARQL queries across life science data. RESULTS: We introduce a novel SPARQL-based service to enable on-the-fly integration of life science data. This service uses the identifier patterns defined in the Identifiers.org Registry to generate a plurality of identifier variants, which can then be used to match source identifiers with target identifiers. We demonstrate the utility of this identifier integration approach by answering queries across major producers of life science Linked Data. AVAILABILITY AND IMPLEMENTATION: The SPARQL-based identifier conversion service is available without restriction at http://identifiers.org/services/sparql.

MOTIVATION: Resource description framework (RDF) is an emerging technology for describing, publishing and linking life science data. As a major provider of bioinformatics data and services, the European Bioinformatics Institute (EBI) is committed to making data readily accessible to the community in ways that meet existing demand. The EBI RDF platform has been developed to meet an increasing demand to coordinate RDF activities across the institute and provides a new entry point to querying and exploring integrated resources available at the EBI.

BACKGROUND: The UniProt consortium was formed in 2002 by groups from the Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) at Georgetown University, and soon afterwards the website http://www.uniprot.org was set up as a central entry point to UniProt resources. Requests to this address were redirected to one of the three organisations' websites. While these sites shared a set of static pages with general information about UniProt, their pages for searching and viewing data were different. To provide users with a consistent view and to cut the cost of maintaining three separate sites, the consortium decided to develop a common website for UniProt. Following several years of intense development and a year of public beta testing, the http://www.uniprot.org domain was switched to the newly developed site described in this paper in July 2008. DESCRIPTION: The UniProt consortium is the main provider of protein sequence and annotation data for much of the life sciences community. The http://www.uniprot.org website is the primary access point to this data and to documentation and basic tools for the data. These tools include full text and field-based text search, similarity search, multiple sequence alignment, batch retrieval and database identifier mapping. This paper discusses the design and implementation of the new website, which was released in July 2008, and shows how it improves data access for users with different levels of experience, as well as to machines for programmatic access.http://www.uniprot.org/ is open for both academic and commercial use. The site was built with open source tools and libraries. Feedback is very welcome and should be sent to [email protected]. CONCLUSION: The new UniProt website makes accessing and understanding UniProt easier than ever. The two main lessons learned are that getting the basics right for such a data provider website has huge benefits, but is not trivial and easy to underestimate, and that there is no substitute for using empirical data throughout the development process to decide on what is and what is not working for your users.

SUMMARY: The EMBL Nucleotide Sequence Database, maintained at the European Bioinformatics institute, is Europe's primary nucleotide sequences database. Its entries are subject to changes, but only the most recent versions are preserved in the database. The EMBL Sequence Version Archive is a new publicly available database retaining also the earlier versions of these entries. AVAILABILITY: http://www.ebi.ac.uk/embl/sva/

UNLABELLED: The submission of multiple sequence alignment data to EMBL has grown 30-fold in the past 10 years, creating a problem of archiving them. The EBI has developed a new public database of multiple sequence alignments called EMBL-Align. It has a dedicated web-based submission tool, Webin-Align. Together they represent a comprehensive data management solution for alignment data. Webin-Align accepts all the common alignment formats and can display data in CLUSTALW format as well as a new standard EMBL-Align flat file format. The alignments are stored in the EMBL-Align database and can be queried from the EBI SRS (Sequence Retrieval System) server. AVAILABILITY: Webin-Align: http://www.ebi.ac.uk/embl/Submission/align_top.html, EMBL-Align: ftp://ftp.ebi.ac.uk/pub/databases/embl/align, http://srs.ebi.ac.uk/

This paper describes a new tool enabling awareness of new sequence databank entries of interest. The FastAlert system relieves the researcher from the burden of repeating FASTA searches in order to keep up with the rapidly growing amount of information found in biological sequence databanks. The query sequence can be submitted from any computer connected to the Internet. Upon registration, the databank, including the updates, is scanned at periodic intervals with the sequence provided. The results, so-called FastAlert reports, are delivered via electronic mail. The reports contain the FASTA best-scores list and the similarity statistics for each entry listed.