The European Bioinformatics Institute (EMBL-EBI) in 2021.

The European Bioinformatics Institute (EMBL-EBI) maintains a comprehensive range of freely available and up-to-date molecular data resources, which includes over 40 resources covering every major data type in the life sciences. This year's service update for EMBL-EBI includes new resources, PGS Catalog and AlphaFold DB, and updates on existing resources, including the COVID-19 Data Platform, trRosetta and RoseTTAfold models introduced in Pfam and InterPro, and the launch of Genome Integrations with Function and Sequence by UniProt and Ensembl. Furthermore, we highlight projects through which EMBL-EBI has contributed to the development of community-driven data standards and guidelines, including the Recommended Metadata for Biological Images (REMBI), and the BioModels Reproducibility Scorecard. Training is one of EMBL-EBI's core missions and a key component of the provision of bioinformatics services to users: this year's update includes many of the improvements that have been developed to EMBL-EBI's online training offering.

The European Bioinformatics Institute: empowering cooperation in response to a global health crisis.

The European Bioinformatics Institute (EMBL-EBI; https://www.ebi.ac.uk/) provides freely available data and bioinformatics services to the scientific community, alongside its research activity and training provision. The 2020 COVID-19 pandemic has brought to the forefront a need for the scientific community to work even more cooperatively to effectively tackle a global health crisis. EMBL-EBI has been able to build on its position to contribute to the fight against COVID-19 in a number of ways. Firstly, EMBL-EBI has used its infrastructure, expertise and network of international collaborations to help build the European COVID-19 Data Platform (https://www.covid19dataportal.org/), which brings together COVID-19 biomolecular data and connects it to researchers, clinicians and public health professionals. By September 2020, the COVID-19 Data Platform has integrated in excess of 170 000 COVID-19 biomolecular data and literature records, collected through a number of EMBL-EBI resources. Secondly, EMBL-EBI has strived to continue its support of the life science communities through the crisis, with updated Training provision and improved service provision throughout its resources. The COVID-19 pandemic has highlighted the importance of EMBL-EBI's core principles, including international cooperation, resource sharing and central data brokering, and has further empowered scientific cooperation.

The COVID-19 Data Portal: accelerating SARS-CoV-2 and COVID-19 research through rapid open access data sharing.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic will be remembered as one of the defining events of the 21st century. The rapid global outbreak has had significant impacts on human society and is already responsible for millions of deaths. Understanding and tackling the impact of the virus has required a worldwide mobilisation and coordination of scientific research. The COVID-19 Data Portal (https://www.covid19dataportal.org/) was first released as part of the European COVID-19 Data Platform, on April 20th 2020 to facilitate rapid and open data sharing and analysis, to accelerate global SARS-CoV-2 and COVID-19 research. The COVID-19 Data Portal has fortnightly feature releases to continue to add new data types, search options, visualisations and improvements based on user feedback and research. The open datasets and intuitive suite of search, identification and download services, represent a truly FAIR (Findable, Accessible, Interoperable and Reusable) resource that enables researchers to easily identify and quickly obtain the key datasets needed for their COVID-19 research.

The European Bioinformatics Institute in 2020: building a global infrastructure of interconnected data resources for the life sciences.

Data resources at the European Bioinformatics Institute (EMBL-EBI, https://www.ebi.ac.uk/) archive, organize and provide added-value analysis of research data produced around the world. This year's update for EMBL-EBI focuses on data exchanges among resources, both within the institute and with a wider global infrastructure. Within EMBL-EBI, data resources exchange data through a rich network of data flows mediated by automated systems. This network ensures that users are served with as much information as possible from any search and any starting point within EMBL-EBI's websites. EMBL-EBI data resources also exchange data with hundreds of other data resources worldwide and collectively are a key component of a global infrastructure of interconnected life sciences data resources. We also describe the BioImage Archive, a deposition database for raw images derived from primary research that will supply data for future knowledgebases that will add value through curation of primary image data. We also report a new release of the PRIDE database with an improved technical infrastructure, a new API, a new webpage, and improved data exchange with UniProt and Expression Atlas. Training is a core mission of EMBL-EBI and in 2018 our training team served more users, both in-person and through web-based programmes, than ever before.

The European Bioinformatics Institute in 2018: tools, infrastructure and training.

The European Bioinformatics Institute (https://www.ebi.ac.uk/) archives, curates and analyses life sciences data produced by researchers throughout the world, and makes these data available for re-use globally (https://www.ebi.ac.uk/). Data volumes continue to grow exponentially: total raw storage capacity now exceeds 160 petabytes, and we manage these increasing data flows while maintaining the quality of our services. This year we have improved the efficiency of our computational infrastructure and doubled the bandwidth of our connection to the worldwide web. We report two new data resources, the Single Cell Expression Atlas (https://www.ebi.ac.uk/gxa/sc/), which is a component of the Expression Atlas; and the PDBe-Knowledgebase (https://www.ebi.ac.uk/pdbe/pdbe-kb), which collates functional annotations and predictions for structure data in the Protein Data Bank. Additionally, Europe PMC (http://europepmc.org/) has added preprint abstracts to its search results, supplementing results from peer-reviewed publications. EMBL-EBI maintains over 150 analytical bioinformatics tools that complement our data resources. We make these tools available for users through a web interface as well as programmatically using application programming interfaces, whilst ensuring the latest versions are available for our users. Our training team, with support from all of our staff, continued to provide on-site, off-site and web-based training opportunities for thousands of researchers worldwide this year.

The European Bioinformatics Institute in 2017: data coordination and integration.

The European Bioinformatics Institute (EMBL-EBI) supports life-science research throughout the world by providing open data, open-source software and analytical tools, and technical infrastructure (https://www.ebi.ac.uk). We accommodate an increasingly diverse range of data types and integrate them, so that biologists in all disciplines can explore life in ever-increasing detail. We maintain over 40 data resources, many of which are run collaboratively with partners in 16 countries (https://www.ebi.ac.uk/services). Submissions continue to increase exponentially: our data storage has doubled in less than two years to 120 petabytes. Recent advances in cellular imaging and single-cell sequencing techniques are generating a vast amount of high-dimensional data, bringing to light new cell types and new perspectives on anatomy. Accordingly, one of our main focus areas is integrating high-quality information from bioimaging, biobanking and other types of molecular data. This is reflected in our deep involvement in Open Targets, stewarding of plant phenotyping standards (MIAPPE) and partnership in the Human Cell Atlas data coordination platform, as well as the 2017 launch of the Omics Discovery Index. This update gives a birds-eye view of EMBL-EBI's approach to data integration and service development as genomics begins to enter the clinic.

The European Bioinformatics Institute in 2016: Data growth and integration.

New technologies are revolutionising biological research and its applications by making it easier and cheaper to generate ever-greater volumes and types of data. In response, the services and infrastructure of the European Bioinformatics Institute (EMBL-EBI, www.ebi.ac.uk) are continually expanding: total disk capacity increases significantly every year to keep pace with demand (75 petabytes as of December 2015), and interoperability between resources remains a strategic priority. Since 2014 we have launched two new resources: the European Variation Archive for genetic variation data and EMPIAR for two-dimensional electron microscopy data, as well as a Resource Description Framework platform. We also launched the Embassy Cloud service, which allows users to run large analyses in a virtual environment next to EMBL-EBI's vast public data resources.

The European Bioinformatics Institute's data resources 2014.

Molecular Biology has been at the heart of the 'big data' revolution from its very beginning, and the need for access to biological data is a common thread running from the 1965 publication of Dayhoff's 'Atlas of Protein Sequence and Structure' through the Human Genome Project in the late 1990s and early 2000s to today's population-scale sequencing initiatives. The European Bioinformatics Institute (EMBL-EBI; http://www.ebi.ac.uk) is one of three organizations worldwide that provides free access to comprehensive, integrated molecular data sets. Here, we summarize the principles underpinning the development of these public resources and provide an overview of EMBL-EBI's database collection to complement the reviews of individual databases provided elsewhere in this issue.

Integration of cardiac proteome biology and medicine by a specialized knowledgebase.

RATIONALE: Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. OBJECTIVE: The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. METHODS AND RESULTS: We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans, as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. CONCLUSIONS: COPaKB provides an innovative and interactive resource that connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified Web server, nonproteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes.

Prepublication data sharing.

Rapid release of prepublication data has served the field of genomics well. Attendees at a workshop in Toronto recommend extending the practice to other biological data sets.

Characterization, design, and function of the mitochondrial proteome: from organs to organisms.

Mitochondria are a common energy source for organs and organisms; their diverse functions are specialized according to the unique phenotypes of their hosting environment. Perturbation of mitochondrial homeostasis accompanies significant pathological phenotypes. However, the connections between mitochondrial proteome properties and function remain to be experimentally established on a systematic level. This uncertainty impedes the contextualization and translation of proteomic data to the molecular derivations of mitochondrial diseases. We present a collection of mitochondrial features and functions from four model systems, including two cardiac mitochondrial proteomes from distinct genomes (human and mouse), two unique organ mitochondrial proteomes from identical genetic codons (mouse heart and mouse liver), as well as a relevant metazoan out-group (drosophila). The data, composed of mitochondrial protein abundance and their biochemical activities, capture the core functionalities of these mitochondria. This investigation allowed us to redefine the core mitochondrial proteome from organs and organisms, as well as the relevant contributions from genetic information and hosting milieu. Our study has identified significant enrichment of disease-associated genes and their products. Furthermore, correlational analyses suggest that mitochondrial proteome design is primarily driven by cellular environment. Taken together, these results connect proteome feature with mitochondrial function, providing a prospective resource for mitochondrial pathophysiology and developing novel therapeutic targets in medicine.

InterPro in 2011: new developments in the family and domain prediction database.

InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.

Linking publication, gene and protein data.

The computational reconstruction of biological systems, 'systems biology', is necessarily dependent on the existence of well-annotated data sets defining and describing the components of these systems, especially genes and the proteins they encode. Information about these components can be accessed either through structured bioinformatics databases, which store basic chemical and functional information abstracted from (or supplementing) the scientific literature, or through the literature itself, which is richer in content but essentially unstructured.

Phosphoproteome analysis reveals regulatory sites in major pathways of cardiac mitochondria.

Mitochondrial functions are dynamically regulated in the heart. In particular, protein phosphorylation has been shown to be a key mechanism modulating mitochondrial function in diverse cardiovascular phenotypes. However, site-specific phosphorylation information remains scarce for this organ. Accordingly, we performed a comprehensive characterization of murine cardiac mitochondrial phosphoproteome in the context of mitochondrial functional pathways. A platform using the complementary fragmentation technologies of collision-induced dissociation (CID) and electron transfer dissociation (ETD) demonstrated successful identification of a total of 236 phosphorylation sites in the murine heart; 210 of these sites were novel. These 236 sites were mapped to 181 phosphoproteins and 203 phosphopeptides. Among those identified, 45 phosphorylation sites were captured only by CID, whereas 185 phosphorylation sites, including a novel modification on ubiquinol-cytochrome c reductase protein 1 (Ser-212), were identified only by ETD, underscoring the advantage of a combined CID and ETD approach. The biological significance of the cardiac mitochondrial phosphoproteome was evaluated. Our investigations illustrated key regulatory sites in murine cardiac mitochondrial pathways as targets of phosphorylation regulation, including components of the electron transport chain (ETC) complexes and enzymes involved in metabolic pathways (e.g. tricarboxylic acid cycle). Furthermore, calcium overload injured cardiac mitochondrial ETC function, whereas enhanced phosphorylation of ETC via application of phosphatase inhibitors restored calcium-attenuated ETC complex I and complex III activities, demonstrating positive regulation of ETC function by phosphorylation. Moreover, in silico analyses of the identified phosphopeptide motifs illuminated the molecular nature of participating kinases, which included several known mitochondrial kinases (e.g. pyruvate dehydrogenase kinase) as well as kinases whose mitochondrial location was not previously appreciated (e.g. Src). In conclusion, the phosphorylation events defined herein advance our understanding of cardiac mitochondrial biology, facilitating the integration of the still fragmentary knowledge about mitochondrial signaling networks, metabolic pathways, and intrinsic mechanisms of functional regulation in the heart.

The HUPO initiative on Model Organism Proteomes, iMOP.

The community working on model organisms is growing steadily and the number of model organisms for which proteome data are being generated is continuously increasing. To standardize efforts and to make optimal use of proteomics data acquired from model organisms, a new Human Proteome Organisation (HUPO) initiative on model organism proteomes (iMOP) was approved at the HUPO Ninth Annual World Congress in Sydney, 2010. iMOP will seek to stimulate scientific exchange and disseminate HUPO best practices. The needs of model organism researchers for central databases will be better represented, catalyzing the integration of proteomics and organism-specific databases. Full details of iMOP activities, members, tools and resources can be found at our website http://www.imop.uzh.ch/ and new members are invited to join us.

Data Mining, Quality and Management in the Life Sciences.

With the evermore emphasis put on open science and its invaluable benefits to the scientific community, it is no longer the case where a research project simply ends with a scientific publication. The benefits of data sharing and reproducibility of results have taken the centerpiece within the life science research supported by FAIR principles that firmly underline the importance of open data. The current data-intensive multidisciplinary research has also highlighted the significance of how data is mined and managed. Here we describe some of the features adopted by EMBL-EBI data resources to support data mining, data quality, and data management. We also highlight how EMBL-EBI has responded to the current pandemic through its data resources.

Consequences of the discontinuation of the International Protein Index (IPI) database and its substitution by the UniProtKB "complete proteome" sets.

The International Protein Index (IPI) database has been one of the most widely used protein databases in MS proteomics approaches. Recently, the closure of IPI in September 2011 was announced. Its recommended replacement is the new UniProt Knowledgebase (UniProtKB) "complete proteome" sets, launched in May 2011. Here, we analyze the consequences of IPI's discontinuation for human and mouse data, and the effect of its substitution with UniProtKB on two levels: (i) data already produced and (ii) newly performed experiments. To estimate the effect on existing data, we investigated how well IPI identifiers map to UniProtKB accessions. We found that 21% of human and 10% of mouse identifiers do not map to UniProtKB and would thus be "lost." To investigate the impact on new experiments, we compared the theoretical search space (i.e. the tryptic peptides) of both resources and found that it is decreased by 14.0% for human and 8.9% for mouse data through IPI's closure. An analysis on the experimental evidence for these "lost" peptides showed that the vast majority has not been identified in experiments available in the major proteomics repositories. It thus seems likely that the search space provided by UniProtKB is of higher quality than the one currently provided by IPI.

A posteriori quality control for the curation and reuse of public proteomics data.

Proteomics is a rapidly expanding field encompassing a multitude of complex techniques and data types. To date much effort has been devoted to achieving the highest possible coverage of proteomes with the aim to inform future developments in basic biology as well as in clinical settings. As a result, growing amounts of data have been deposited in publicly available proteomics databases. These data are in turn increasingly reused for orthogonal downstream purposes such as data mining and machine learning. These downstream uses however, need ways to a posteriori validate whether a particular data set is suitable for the envisioned purpose. Furthermore, the (semi-)automatic curation of repository data is dependent on analyses that can highlight misannotation and edge conditions for data sets. Such curation is an important prerequisite for efficient proteomics data reuse in the life sciences in general. We therefore present here a selection of quality control metrics and approaches for the a posteriori detection of potential issues encountered in typical proteomics data sets. We illustrate our metrics by relying on publicly available data from the Proteomics Identifications Database (PRIDE), and simultaneously show the usefulness of the large body of PRIDE data as a means to derive empirical background distributions for relevant metrics.

Comparative proteomics profiling reveals role of smooth muscle progenitors in extracellular matrix production.

OBJECTIVE: Recent studies on cardiovascular progenitors have led to a new appreciation that paracrine factors may support the regeneration of damaged tissues. METHODS AND RESULTS: We used a shotgun proteomics strategy to compare the secretome of peripheral blood-derived smooth muscle progenitors (SPCs) with human aortic smooth muscle cells. The late-outgrowth SPCs produced fewer proteolytic enzymes and inflammatory cytokines and showed reduced invasive capacity. Similar to smooth muscle cells, SPCs secreted extracellular matrix. However, SPCs produced different matrix proteins, as evidenced by the truncation of proangiogenic domains in collagen alpha-1 (I) and increased production of periostin. Moreover, SPCs retained serum proteins, including proteoglycans, regulating collagen assembly; and pigment epithelium-derived factor, a potent inhibitor of angiogenesis. As a functional consequence, their conditioned medium was less angiogenic, as demonstrated by endothelial tube formation assays in vitro and implantation of Matrigel plugs into nude, severe combined immunodeficient mice (NOD/SCID). CONCLUSIONS: The present study represents an important conceptual development, suggesting that SPCs may contribute to extracellular matrix production.

The GOA database in 2009--an integrated Gene Ontology Annotation resource.

The Gene Ontology Annotation (GOA) project at the EBI (http://www.ebi.ac.uk/goa) provides high-quality electronic and manual associations (annotations) of Gene Ontology (GO) terms to UniProt Knowledgebase (UniProtKB) entries. Annotations created by the project are collated with annotations from external databases to provide an extensive, publicly available GO annotation resource. Currently covering over 160 000 taxa, with greater than 32 million annotations, GOA remains the largest and most comprehensive open-source contributor to the GO Consortium (GOC) project. Over the last five years, the group has augmented the number and coverage of their electronic pipelines and a number of new manual annotation projects and collaborations now further enhance this resource. A range of files facilitate the download of annotations for particular species, and GO term information and associated annotations can also be viewed and downloaded from the newly developed GOA QuickGO tool (http://www.ebi.ac.uk/QuickGO), which allows users to precisely tailor their annotation set.