Francis Rowland

Bio: Francis Rowland is an academic researcher from European Bioinformatics Institute. The author has contributed to research in topics: Biological data visualization & Web application. The author has an hindex of 8, co-authored 12 publications receiving 739 citations. Previous affiliations of Francis Rowland include Wellcome Trust.

Open Targets: a platform for therapeutic target identification and validation.

Abstract: We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.

The European Genome-phenome Archive of human data consented for biomedical research

Abstract: Paul Flicek and colleagues provide an update on the European Genome-phenome Archive (EGA), a service of the European Bioinformatics Institute (EMBL-EBI) and the Center for Genome Regulation (CRG). The authors describe the EGA policies and infrastructure, how access decisions are made, methods for data submission and future plans for expansion of this database.

Information visualisation for science and policy: engaging users and avoiding bias

Abstract: Visualisations and graphics are fundamental to studying complex subject matter. However, beyond acknowledging this value, scientists and science-policy programmes rarely consider how visualisations can enable discovery, create engaging and robust reporting, or support online resources. Producing accessible and unbiased visualisations from complicated, uncertain data requires expertise and knowledge from science, policy, computing, and design. However, visualisation is rarely found in our scientific training, organisations, or collaborations. As new policy programmes develop [e.g., the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES)], we need information visualisation to permeate increasingly both the work of scientists and science policy. The alternative is increased potential for missed discoveries, miscommunications, and, at worst, creating a bias towards the research that is easiest to display.

Ten simple rules for organizing an unconference

Abstract: An academic conference is a traditional platform for researchers and professionals to network and learn about recent developments and trends in a particular academic field [1–4]. Typically, the organizing committees and sponsors decide the main theme and sub-topics of the conference and select the presenters based on peer-reviewed papers [5]. The selected speakers usually share their research with a large audience by means of presentations and posters. However, the most stimulating discussions generally take place over coffee breaks when attendees can interact with each other and discuss various topics, including their own research interests, in a more informal manner [1, 6, 7], while expanding their own professional networks. An emphasis on facilitating such informal/networking interactions is a central focus of “unconventional conferences”—or “unconferences.” While many people may not yet have taken part in an unconference, the concept has been around for more than two decades. Events with unconference formats, beginning as early as 1985, include Open Space Technology, Foo Camp, BarCamp, Birds of a Feather, EdCamp, ScienceOnline, and many others. The success of these events has made the unconference format increasingly popular and widely known [8–11]. Unlike traditional conferences, an unconference is a participant-oriented meeting where the attendees decide on the agenda, discussion topics, workshops, and, often, even the time and venues. The informal and flexible program allows participants to suggest topics of their own interest and choose sessions accordingly. The format provides an excellent opportunity for researchers from diverse disciplines to work collaboratively on topics of common interest. The overarching goal for most unconferences is to prioritize conversation over presentation. In other words, the content for a session does not come from a select number of individuals at the front of the room, but is generated by all the attendees within the room, and, as such, every participant has an important role. Advantages of the unconference format include: a focus on topics that are relevant to the attendees (because they suggested them), an opportunity for teamwork development, flexibility of schedule, and an emphasis on contributions from every participant. The relationships built during an unconference often continue well past the event. The interactions can lead to productive collaborations, professional development opportunities, and a network of resources and are very effective at building a community amongst participants. The unconference format, therefore, gives participants experience in working together, and this can change how they think about their day-to-day work. A range of articles offer tips and advice for organizing and delivering aspects of scientific conferences and meetings or observations on features of successful meetings [5, 12, 13], including several from the PLOS Computational Biology “Ten Simple Rules” collection [14–16]. While the rules presented in this article are of particular relevance to the organization of unconferences, several of these points are also useful and complementary guidelines for organizing other kinds of events.

BioJS: an open source standard for biological visualisation - its status in 2014.

Abstract: BioJS is a community-based standard and repository of functional components to represent biological information on the web. The development of BioJS has been prompted by the growing need for bioinformatics visualisation tools to be easily shared, reused and discovered. Its modular architecture makes it easy for users to find a specific functionality without needing to know how it has been built, while components can be extended or created for implementing new functionality. The BioJS community of developers currently provides a range of functionality that is open access and freely available. A registry has been set up that categorises and provides installation instructions and testing facilities at http://www.ebi.ac.uk/tools/biojs/. The source code for all components is available for ready use at https://github.com/biojs/biojs.

The PRIDE database and related tools and resources in 2019: improving support for quantification data.

Abstract: The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019.

Abstract: The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

COSMIC: the Catalogue Of Somatic Mutations In Cancer

Abstract: COSMIC, the Catalogue Of Somatic Mutations In Cancer (https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC's deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.

The ChEMBL database in 2017.

Abstract: ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 and 2014 Nucleic Acids Research Database Issues. Since then, alongside the continued extraction of data from the medicinal chemistry literature, new sources of bioactivity data have also been added to the database. These include: deposited data sets from neglected disease screening; crop protection data; drug metabolism and disposition data and bioactivity data from patents. A number of improvements and new features have also been incorporated. These include the annotation of assays and targets using ontologies, the inclusion of targets and indications for clinical candidates, addition of metabolic pathways for drugs and calculation of structural alerts. The ChEMBL data can be accessed via a web-interface, RDF distribution, data downloads and RESTful web-services.

Trends in GPCR drug discovery: new agents, targets and indications

Abstract: G protein-coupled receptors (GPCRs) are the most intensively studied drug targets, mostly due to their substantial involvement in human pathophysiology and their pharmacological tractability. Here, we report an up-to-date analysis of all GPCR drugs and agents in clinical trials, which reveals current trends across molecule types, drug targets and therapeutic indications, including showing that 475 drugs (~34% of all drugs approved by the US Food and Drug Administration (FDA)) act at 108 unique GPCRs. Approximately 321 agents are currently in clinical trials, of which ~20% target 66 potentially novel GPCR targets without an approved drug, and the number of biological drugs, allosteric modulators and biased agonists has increased. The major disease indications for GPCR modulators show a shift towards diabetes, obesity and Alzheimer disease, although several central nervous system disorders are also highly represented. The 224 (56%) non-olfactory GPCRs that have not yet been explored in clinical trials have broad untapped therapeutic potential, particularly in genetic and immune system disorders. Finally, we provide an interactive online resource to analyse and infer trends in GPCR drug discovery.