The European Bioinformatics Institute (EMBL-EBI) in 2021

Cantelli, Gaia; Bateman, Alex; Brooksbank, Cath; Petrov, Anton I.; Malik-Sheriff, Rahuman S.; Ide-Smith, Michele; Hermjakob, Henning; Flicek, Paul; Apweiler, Rolf; Birney, Ewan; McEntyre, Johanna

doi:10.1093/nar/gkab1127

Cited by 36 publications

(15 citation statements)

References 35 publications

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“…As usual, the Issue begins with updates from the major database providers at the European Bioinformatics Institute (EBI), the U.S. National Center for Biotechnology Information (NCBI), and the National Genomics Data Center (NGDC) in China ( 1–3 ). Thereafter, articles are placed in the usual categories: (i) nucleic acid sequence, structure and transcriptional regulation; (ii) protein sequence and structure; (iii) metabolic and signaling pathways, enzymes and networks; (iv) genomics of viruses, bacteria, protozoa and fungi; (v) genomics of human and model organisms plus comparative genomics; (vi) human genomic variation, diseases and drugs; (vii) plants and (viii) other topics, such as proteomics databases.…”

Section: New and Updated Databasesmentioning

confidence: 99%

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

Rigden

Fernández

2021

Nucleic Acids Research

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The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.

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Section: New and Updated Databasesmentioning

confidence: 99%

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

Rigden

Fernández

2021

Nucleic Acids Research

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“…Systematic measurements of biological samples through omics technologies, together with efforts to distil the scientific literature into structured databases, are providing an ever-growing corpus of biomedical and biomolecular information 1 . Indeed, the data stored in the EMBL-EBI has increased sixfold in the last few years, from 40 petabytes in 2014 to over 250 in 2021 2 . Associated with this phenomenon, a variety of nomenclatures have been proposed, along with identifiers, levels of resolution (e.g., protein isoforms or gene splice variants) and experimental conditions, making data integration and harmonization across platforms a challenging step 3 .…”

Section: Introductionmentioning

confidence: 99%

Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque

et al. 2022

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Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a major challenge, so that multiple views of a given biological event can be considered simultaneously. Here we present the Bioteque, a resource of unprecedented size and scope that contains pre-calculated biomedical descriptors derived from a gigantic knowledge graph, displaying more than 450 thousand biological entities and 30 million relationships between them. The Bioteque integrates, harmonizes, and formats data collected from over 150 data sources, including 12 biological entities (e.g., genes, diseases, drugs) linked by 67 types of associations (e.g., ‘drug treats disease’, ‘gene interacts with gene’). We show how Bioteque descriptors facilitate the assessment of high-throughput protein-protein interactome data, the prediction of drug response and new repurposing opportunities, and demonstrate that they can be used off-the-shelf in downstream machine learning tasks without loss of performance with respect to using original data. The Bioteque thus offers a thoroughly processed, tractable, and highly optimized assembly of the biomedical knowledge available in the public domain.

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“…Systematic measurements of biological samples through ‘omics’ technologies, together with efforts to distill the scientific literature into structured databases, are providing an ever-growing corpus of biomedical and biomolecular information 1 . Indeed, the data stored in the EMBL-EBI has increased sixfold in the last few years, from 40 petabytes in 2014 to over 250 in 2021 2 . Associated with this phenomenon, a variety of nomenclatures have been proposed, along with identifiers, levels of resolution (e.g., protein isoforms or gene splicing variants) and experimental conditions, making data integration and harmonization across platforms a challenging step 3 .…”

Section: Introductionmentioning

confidence: 99%

Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque

Fernández‐Torras

Duran‐Frigola

Bertoni

et al. 2022

Preprint

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Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a major challenge, so that multiple views of a given biological event can be considered simultaneously. Here we present the Bioteque, a resource of unprecedented size and scope that contains pre-calculated biomedical embeddings derived from a gigantic knowledge graph, displaying more than 450 thousand biological entities and 30 million relationships between them. The Bioteque integrates, harmonizes and formats data collected from over 150 data sources, including 12 biological entities (e.g., genes, diseases, drugs) linked by 67 types of associations (e.g., ‘drug treats disease’, ‘gene interacts with gene’). We show how Bioteque embeddings facilitate the assessment of high-throughput interactome data, pharmacogenomics and drug repurposing exercises, and demonstrate that they can be used off-the-shelf in downstream machine learning tasks without loss of performance with respect to using original data. The Bioteque thus offers a thoroughly processed, tractable, and highly optimized assembly of the biomedical knowledge available in the public domain.

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The European Bioinformatics Institute (EMBL-EBI) in 2021

Cited by 36 publications

References 35 publications

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque

Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque

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