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The European Bioinformatics Institute On the way to realising the full potential of PIDs in BioSciences: THOR work at EMBl-EBI Robert Petryszak Gene Expression Team Leader EMBL-EBI What is EMBL-EBI? • Europe’s home for biological data services, research and training • A trusted data provider for the life sciences – both academia and industry • Part of the European Molecular Biology Laboratory, an intergovernmental research organisation • International: 570 members of staff from 57 nations • Home of the ELIXIR Technical hub Data resources at EMBL-EBI – THOR participants Genes, genomes & variation European Nucleotide Archive Ensembl GWAS Catalog European Variation Archive Ensembl Metagenomics portal European Genome-phenome ArchiveGenomes Gene, protein & metabolite expression RNA Central Expression Atlas PRIDE Systems ArrayExpress Metabolights BioModels BioSamples Protein sequences, families & Enzyme Portal IntAct/Complex motifs InterPro Pfam/Rfam UniProt Portal Reactome Molecular structures Protein Data Bank in Europe Literature & Electron Microscopy Data Bank ontologies Chemical biology Europe PubMed Central BioStudies ChEMBL SureChEMBL ChEBI Gene Ontology Experimental Factor Ontology Identifers.org EMBL-EBI THOR Development – At a Glance Claiming Individual Studies Batch Retrospective Claiming Linked Research Visualisation Examples – Researchers – ArrayExpress studies - Funders Synergistic Efforts at EMBL-EBI http://www.omicsdi.org/search Synergistic Efforts at EMBL-EBI http://www.omicsdi.org/search Synergistic Efforts at EMBL-EBI http://www.omicsdi.org/search Search Europe PMC By ORCID EBI ORCID HUB ORCID Protein Data Bank - Submitter Profile: Submission Timeline Widget identifiers.org Acknowledgements • Jo McEntyre, Guilherme Mello, Florian Graef – Europe PMC • Sarala Wilamaratne, Henning Hermjakob – identifiers.org • EMBL-EBI teams implementing THOR functionality: • ArrayExpress, PDB, • PRIDE, OmicsDI, • Intact, BioStudies, • GWAS Catalogue, Pfam/Rfam, • EBI Search • All my THOR collaborators.

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The ELIXIR Core Data Resources: Fundamental Infrastructure for The
Supplementary Data: The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences The “Supporting Material” referred to within this Supplementary Data can be found in the Supporting.Material.CDR.infrastructure file, DOI: 10.5281/zenodo.2625247 (https://zenodo.org/record/2625247). Figure 1. Scale of the Core Data Resources Table S1. Data from which Figure 1 is derived: Year 2013 2014 2015 2016 2017 Data entries 765881651 997794559 1726529931 1853429002 2715599247 Monthly user/IP addresses 1700660 2109586 2413724 2502617 2867265 FTEs 270 292.65 295.65 289.7 311.2 Figure 1 includes data from the following Core Data Resources: ArrayExpress, BRENDA, CATH, ChEBI, ChEMBL, EGA, ENA, Ensembl, Ensembl Genomes, EuropePMC, HPA, IntAct /MINT , InterPro, PDBe, PRIDE, SILVA, STRING, UniProt ● Note that Ensembl’s compute infrastructure physically relocated in 2016, so “Users/IP address” data are not available for that year. In this case, the 2015 numbers were rolled forward to 2016. ● Note that STRING makes only minor releases in 2014 and 2016, in that the interactions are re-computed, but the number of “Data entries” remains unchanged. The major releases that change the number of “Data entries” happened in 2013 and 2015. So, for “Data entries” , the number for 2013 was rolled forward to 2014, and the number for 2015 was rolled forward to 2016. The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences 1 Figure 2: Usage of Core Data Resources in research The following steps were taken: 1. API calls were run on open access full text articles in Europe PMC to identify articles that mention Core Data Resource by name or include specific data record accession numbers.
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Methods in and Applications of the Sequencing of Short Non-Coding Rnas" (2013)
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2013 Methods in and Applications of the Sequencing of Short Non- Coding RNAs Paul Ryvkin University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Genetics Commons, and the Molecular Biology Commons Recommended Citation Ryvkin, Paul, "Methods in and Applications of the Sequencing of Short Non-Coding RNAs" (2013). Publicly Accessible Penn Dissertations. 922. https://repository.upenn.edu/edissertations/922 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/922 For more information, please contact [email protected]. Methods in and Applications of the Sequencing of Short Non-Coding RNAs Abstract Short non-coding RNAs are important for all domains of life. With the advent of modern molecular biology their applicability to medicine has become apparent in settings ranging from diagonistic biomarkers to therapeutics and fields angingr from oncology to neurology. In addition, a critical, recent technological development is high-throughput sequencing of nucleic acids. The convergence of modern biotechnology with developments in RNA biology presents opportunities in both basic research and medical settings. Here I present two novel methods for leveraging high-throughput sequencing in the study of short non- coding RNAs, as well as a study in which they are applied to Alzheimer's Disease (AD). The computational methods presented here include High-throughput Annotation of Modified Ribonucleotides (HAMR), which enables researchers to detect post-transcriptional covalent modifications ot RNAs in a high-throughput manner. In addition, I describe Classification of RNAs by Analysis of Length (CoRAL), a computational method that allows researchers to characterize the pathways responsible for short non-coding RNA biogenesis.
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Comparing Tools for Non-Coding RNA Multiple Sequence Alignment Based On
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EMBL-European Bioinformatics Institute Annual Scientific Report 2013 On the cover Structure 3fof in the Protein Data Bank, determined by Laponogov, I. et al. (2009) Structural insight into the quinolone-DNA cleavage complex of type IIA topoisomerases. Nature Structural & Molecular Biology 16, 667-669. © 2014 European Molecular Biology Laboratory This publication was produced by the External Relations team at the European Bioinformatics Institute (EMBL-EBI) A digital version of the brochure can be found at www.ebi.ac.uk/about/brochures For more information about EMBL-EBI please contact: [email protected] Contents Introduction & overview 3 Services 8 Genes, genomes and variation 8 Molecular atlas 12 Proteins and protein families 14 Molecular and cellular structures 18 Chemical biology 20 Molecular systems 22 Cross-domain tools and resources 24 Research 26 Support 32 ELIXIR 36 Facts and figures 38 Funding & resource allocation 38 Growth of core resources 40 Collaborations 42 Our staff in 2013 44 Scientific advisory committees 46 Major database collaborations 50 Publications 52 Organisation of EMBL-EBI leadership 61 2013 EMBL-EBI Annual Scientific Report 1 Foreword Welcome to EMBL-EBI’s 2013 Annual Scientific Report. Here we look back on our major achievements during the year, reflecting on the delivery of our world-class services, research, training, industry collaboration and European coordination of life-science data. The past year has been one full of exciting changes, both scientifically and organisationally. We unveiled a new website that helps users explore our resources more seamlessly, saw the publication of ground-breaking work in data storage and synthetic biology, joined the global alliance for global health, built important new relationships with our partners in industry and celebrated the launch of ELIXIR.
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A Unicellular Relative of Animals Generates a Layer of Polarized Cells
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The Pfam Protein Families Database Marco Punta1,*, Penny C
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MEROPS: the Peptidase Database Neil D
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Rfam 14: Expanded Coverage of Metagenomic, Viral and Microrna Families Ioanna Kalvari, Eric P
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Comparing Tools for Noncoding RNA Multiple Sequence Alignment Based on Structural Consistency
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Structure-Based Realignment of Non-Coding Rnas in Multiple Whole Genome Alignments
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