Leading the Way
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Uniprot at EMBL-EBI's Role in CTTV
Barbara P. Palka, Daniel Gonzalez, Edd Turner, Xavier Watkins, Maria J. Martin, Claire O’Donovan European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK UniProt at EMBL-EBI’s role in CTTV: contributing to improved disease knowledge Introduction The mission of UniProt is to provide the scientific community with a The Centre for Therapeutic Target Validation (CTTV) comprehensive, high quality and freely accessible resource of launched in Dec 2015 a new web platform for life- protein sequence and functional information. science researchers that helps them identify The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of therapeutic targets for new and repurposed medicines. functional information on proteins, with accurate, consistent and rich CTTV is a public-private initiative to generate evidence on the annotation. As much annotation information as possible is added to each validity of therapeutic targets based on genome-scale experiments UniProtKB record and this includes widely accepted biological ontologies, and analysis. CTTV is working to create an R&D framework that classifications and cross-references, and clear indications of the quality of applies to a wide range of human diseases, and is committed to annotation in the form of evidence attribution of experimental and sharing its data openly with the scientific community. CTTV brings computational data. together expertise from four complementary institutions: GSK, Biogen, EMBL-EBI and Wellcome Trust Sanger Institute. UniProt’s disease expert curation Q5VWK5 (IL23R_HUMAN) This section provides information on the disease(s) associated with genetic variations in a given protein. The information is extracted from the scientific literature and diseases that are also described in the OMIM database are represented with a controlled vocabulary. -
ANNUAL REVIEW 1 October 2005–30 September
WELLCOME TRUST ANNUAL REVIEW 1 October 2005–30 September 2006 ANNUAL REVIEW 2006 The Wellcome Trust is the largest charity in the UK and the second largest medical research charity in the world. It funds innovative biomedical research, in the UK and internationally, spending around £500 million each year to support the brightest scientists with the best ideas. The Wellcome Trust supports public debate about biomedical research and its impact on health and wellbeing. www.wellcome.ac.uk THE WELLCOME TRUST The Wellcome Trust is the largest charity in the UK and the second largest medical research charity in the world. 123 CONTENTS BOARD OF GOVERNORS 2 Director’s statement William Castell 4 Advancing knowledge Chairman 16 Using knowledge Martin Bobrow Deputy Chairman 24 Engaging society Adrian Bird 30 Developing people Leszek Borysiewicz 36 Facilitating research Patricia Hodgson 40 Developing our organisation Richard Hynes 41 Wellcome Trust 2005/06 Ronald Plasterk 42 Financial summary 2005/06 Alastair Ross Goobey 44 Funding developments 2005/06 Peter Smith 46 Streams funding 2005/06 Jean Thomas 48 Technology Transfer Edward Walker-Arnott 49 Wellcome Trust Genome Campus As at January 2007 50 Public Engagement 51 Library and information resources 52 Advisory committees Images 1 Surface of the gut. 3 Zebrafish. 5 Cells in a developing This Annual Review covers the 2 Young children in 4 A scene from Y fruit fly. Wellcome Trust’s financial year, from Kenya. Touring’s Every Breath. 6 Data management at the Sanger Institute. 1 October 2005 to 30 September 2006. CONTENTS 1 45 6 EXECUTIVE BOARD MAKING A DIFFERENCE Developing people: To foster a Mark Walport The Wellcome Trust’s mission is research community and individual Director to foster and promote research with researchers who can contribute to the advancement and use of knowledge Ted Bianco the aim of improving human and Director of Technology Transfer animal health. -
Analysis of the Impact of Sequencing Errors on Blast Using Fault Injection
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Illinois Digital Environment for Access to Learning and Scholarship Repository ANALYSIS OF THE IMPACT OF SEQUENCING ERRORS ON BLAST USING FAULT INJECTION BY SO YOUN LEE THESIS Submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Computer Engineering in the Graduate College of the University of Illinois at Urbana-Champaign, 2013 Urbana, Illinois Adviser: Professor Ravishankar K. Iyer ABSTRACT This thesis investigates the impact of sequencing errors in post-sequence computational analyses, including local alignment search and multiple sequence alignment. While the error rates of sequencing technology are commonly reported, the significance of these numbers cannot be fully grasped without putting them in the perspective of their impact on the downstream analyses that are used for biological research, forensics, diagnosis of diseases, etc. I approached the quantification of the impact using fault injection. Faults were injected in the input sequence data, and the analyses were run. Change in the output of the analyses was interpreted as the impact of faults, or errors. Three commonly used algorithms were used: BLAST, SSEARCH, and ProbCons. The main contributions of this work are the application of fault injection to the reliability analysis in bioinformatics and the quantitative demonstration that a small error rate in the sequence data can alter the output of the analysis in a significant way. BLAST and SSEARCH are both local alignment search tools, but BLAST is a heuristic implementation, while SSEARCH is based on the optimal Smith-Waterman algorithm. -
Advancing Solutions to the Carbohydrate Sequencing Challenge † † † ‡ § Christopher J
Perspective Cite This: J. Am. Chem. Soc. 2019, 141, 14463−14479 pubs.acs.org/JACS Advancing Solutions to the Carbohydrate Sequencing Challenge † † † ‡ § Christopher J. Gray, Lukasz G. Migas, Perdita E. Barran, Kevin Pagel, Peter H. Seeberger, ∥ ⊥ # ⊗ ∇ Claire E. Eyers, Geert-Jan Boons, Nicola L. B. Pohl, Isabelle Compagnon, , × † Göran Widmalm, and Sabine L. Flitsch*, † School of Chemistry & Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, U.K. ‡ Institute for Chemistry and Biochemistry, Freie Universitaẗ Berlin, Takustraße 3, 14195 Berlin, Germany § Biomolecular Systems Department, Max Planck Institute for Colloids and Interfaces, Am Muehlenberg 1, 14476 Potsdam, Germany ∥ Department of Biochemistry, Institute of Integrative Biology, University of Liverpool, Crown Street, Liverpool L69 7ZB, U.K. ⊥ Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia 30602, United States # Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States ⊗ Institut Lumierè Matiere,̀ UMR5306 UniversitéLyon 1-CNRS, Universitéde Lyon, 69622 Villeurbanne Cedex, France ∇ Institut Universitaire de France IUF, 103 Blvd St Michel, 75005 Paris, France × Department of Organic Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden *S Supporting Information established connection between their structure and their ABSTRACT: Carbohydrates possess a variety of distinct function, full characterization of unknown carbohydrates features with -
100000 Genomes and Genomics England
100,000 Genomes & Genomics England Tim Hubbard Genomics England King’s College London, King’s Health Partners Wellcome Trust Sanger Institute Global Leaders in Genomic Medicine Washington 8-9th January 2014 UK Health System 101 • Four separate health services – NHS England – NHS Wales – NHS Scotland – Health & Social Care in Northern Ireland (HSC) • NHS (England) – ~1.4 million employees – ~£110 billion annual budget • Structure in England changed 1st April 2013 https://www.gov.uk/government/organisations/department-of-health Linking Health data to Research Clinical Data Healthcare Professional World Genotype Electronic Health Record Whole Genome Sequencing Phenotype Electronic Genomic Biology Health Data World Records Reference Genotype and genome sequence Phenotype ~3 gigabytes relationship capture EBI: repositories (petabytes of genome sequence data) Human sequence data Sanger: sequencing repositories (1000 genomes, uk10K) Steps in UK towards E-Health Research, Genomic Medicine • Health data to Research – 2006 Creation of OSCHR • Increase coordination between funders: MRC and NIHR – 2007 OSCHR E-health board • Enable research access to UK EHR data • Build capacity for research on EHR data • Genomics to Health – 2009 House of Lords report on Genomic Medicine – 2010 Creation of Human Genomic Strategy Group (HGSG) 2011: UK Life Sciences Strategy No10: http://www.number10.gov.uk/news/uk-life-sciences-get-government-cash-boost/ BIS/DH: http://www.dh.gov.uk/health/2011/12/nhs-adopting-innovation/ Linking Health data to Research Clinical Data -
Functional Effects Detailed Research Plan
GeCIP Detailed Research Plan Form Background The Genomics England Clinical Interpretation Partnership (GeCIP) brings together researchers, clinicians and trainees from both academia and the NHS to analyse, refine and make new discoveries from the data from the 100,000 Genomes Project. The aims of the partnerships are: 1. To optimise: • clinical data and sample collection • clinical reporting • data validation and interpretation. 2. To improve understanding of the implications of genomic findings and improve the accuracy and reliability of information fed back to patients. To add to knowledge of the genetic basis of disease. 3. To provide a sustainable thriving training environment. The initial wave of GeCIP domains was announced in June 2015 following a first round of applications in January 2015. On the 18th June 2015 we invited the inaugurated GeCIP domains to develop more detailed research plans working closely with Genomics England. These will be used to ensure that the plans are complimentary and add real value across the GeCIP portfolio and address the aims and objectives of the 100,000 Genomes Project. They will be shared with the MRC, Wellcome Trust, NIHR and Cancer Research UK as existing members of the GeCIP Board to give advance warning and manage funding requests to maximise the funds available to each domain. However, formal applications will then be required to be submitted to individual funders. They will allow Genomics England to plan shared core analyses and the required research and computing infrastructure to support the proposed research. They will also form the basis of assessment by the Project’s Access Review Committee, to permit access to data. -
Genomics England and Sciencewise Evaluation of a Public Dialogue On
Genomics England and Sciencewise Evaluation of a public dialogue on Genomic Medicine: Time for a new social contract? Evaluation report June 2019 Quality Management URSUS Consulting Ltd has quality systems which have been assessed and approved to BS EN IS9001:2008 (certificate number GB2002687). Creation / Revision History Issue / revision: 3 Date: 19/6/2019 Prepared by: Anna MacGillivray Authorised by: Anna MacGillivray Project number: U.158 File reference: Genomics England/genomic medicine draft evaluation report 19.6.2019 URSUS CONSULTING LTD 57 Balfour Road London N5 2HD Tel. 07989 554 504 www.ursusconsulting.co.uk _________________________________________________________________________________________ URSUS CONSULTING GENOMICS ENGLAND AND SCIENCEWISE 2 Glossary of Acronyms ABI Association of British Insurers AI Artificial Intelligence APBI Association of British Pharmaceutical Industry BEIS (Department of) Business, Energy and Industrial Strategy BME Black and Minority Ethnic CMO Chief Medical Officer CSO (NHS) Chief Scientific Officer DA Devolved Administration DHSC Department of Health and Social Care FTE Full Time Equivalent GDPR General Data Protection Regulation GE Genomics England GG Generation Genome report GMS Genomic medicine service GMC General Medical Council NHS National Health Service OG Oversight Group REA Rapid Evidence Assessment SEG Socio economic group SGP Scottish Genomes Partnership SoS Secretary of State SSAC Scottish Science Advisory Committee SLT Senior Leadership Team UKRI UK Research and Innovation WGS Whole Genome Sequencing _________________________________________________________________________________________ URSUS CONSULTING GENOMICS ENGLAND AND SCIENCEWISE 3 EXECUTIVE SUMMARY Introduction This report of the independent evaluation of a public dialogue on Genomic Medicine: Time for a new social contract? has been prepared by URSUS Consulting Ltd on behalf of Genomics England (GE) and Sciencewise1. -
Rare Variant Contribution to Human Disease in 281,104 UK Biobank Exomes W 1,19 1,19 2,19 2 2 Quanli Wang , Ryan S
https://doi.org/10.1038/s41586-021-03855-y Accelerated Article Preview Rare variant contribution to human disease W in 281,104 UK Biobank exomes E VI Received: 3 November 2020 Quanli Wang, Ryan S. Dhindsa, Keren Carss, Andrew R. Harper, Abhishek N ag, I oa nn a Tachmazidou, Dimitrios Vitsios, Sri V. V. Deevi, Alex Mackay, EDaniel Muthas, Accepted: 28 July 2021 Michael Hühn, Sue Monkley, Henric O ls so n , S eb astian Wasilewski, Katherine R. Smith, Accelerated Article Preview Published Ruth March, Adam Platt, Carolina Haefliger & Slavé PetrovskiR online 10 August 2021 P Cite this article as: Wang, Q. et al. Rare variant This is a PDF fle of a peer-reviewed paper that has been accepted for publication. contribution to human disease in 281,104 UK Biobank exomes. Nature https:// Although unedited, the content has been subjectedE to preliminary formatting. Nature doi.org/10.1038/s41586-021-03855-y (2021). is providing this early version of the typeset paper as a service to our authors and Open access readers. The text and fgures will undergoL copyediting and a proof review before the paper is published in its fnal form. Please note that during the production process errors may be discovered which Ccould afect the content, and all legal disclaimers apply. TI R A D E T A R E L E C C A Nature | www.nature.com Article Rare variant contribution to human disease in 281,104 UK Biobank exomes W 1,19 1,19 2,19 2 2 https://doi.org/10.1038/s41586-021-03855-y Quanli Wang , Ryan S. -
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. -
Volume 21 Supplement a December 2015 Next
EMBnet.journal Volume 21 Supplement A December 2015 Next Generation Sequencing: a look into the future Final Conference & MC Meeting of COST Action BM1006 16-17 March 2015 Bratislava, Slovakia http://seqahead.eu/bratislava_2015 ESF provides COST is supported the Cost Office by the EU RTD through an EC Framework contract Programme EDITORIAL/CONTENT EMBnet.journal 21.A Editorial Contents The key task of COST Action BM1006, SeqAhead, Editorial ..............................................................2 Next Generation Sequencing (NGS) Data Analysis COST Action BM1006 (SeqAhead) closing Network, was, as its name suggests, networking; conference ........................................................3 but SeqAhead also emphasised the dissemina- Scientific Programme.........................................5 tion of knowledge. During the four years of the Keynote Lectures ................................................9 Action, SeqAhead surpassed every expectation: Oral Presentations ........................................... 13 with members participating from 29 European Posters.......................................................................25 countries, plus one international partner from South Africa, the Management Committee mem- bership reads like a “who’s-who” of European NGS research. This EMBnet.journal Conference Supplement clearly shows that during the four years of SeqAhead’s existence, the Action members ac- tively shared software and experiences, and col- laborated in numerous projects spanning diverse EMBnet.journal -
Open Targets Genetics
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.16.299271; this version posted September 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 Open Targets Genetics: An open approach to systematically prioritize causal variants 2 and genes at all published GWAS trait-associated loci 3 4 Edward Mountjoy1,2, Ellen M. Schmidt1,2, Miguel Carmona2,3, Gareth Peat2,3, Alfredo Miranda2,3, 5 Luca Fumis2,3, James Hayhurst2,3, Annalisa Buniello2,3, Jeremy Schwartzentruber1,2,3, Mohd 6 Anisul Karim1,2, Daniel Wright1,2, Andrew Hercules2,3, Eliseo Papa4, Eric Fauman5, Jeffrey C. 7 Barrett1,2, John A. Todd6, David Ochoa2,3, Ian Dunham1,2,3, Maya Ghoussaini1,2,*. 8 9 1. Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 10 1SA, UK 11 2. Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK 12 3. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), 13 Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK 14 4. Systems Biology, Biogen, Cambridge, MA, 02142, United States 15 5. Integrative Biology, Internal Medicine Research Unit, Pfizer Worldwide Research, 16 Development and Medical, Cambridge, MA 02139, United States 17 6. Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford 18 Biomedical Research Centre, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, 19 UK 20 * Corresponding author 21 22 23 24 bioRxiv preprint doi: https://doi.org/10.1101/2020.09.16.299271; this version posted September 17, 2020. -
"Phylogenetic Analysis of Protein Sequence Data Using The
Phylogenetic Analysis of Protein Sequence UNIT 19.11 Data Using the Randomized Axelerated Maximum Likelihood (RAXML) Program Antonis Rokas1 1Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee ABSTRACT Phylogenetic analysis is the study of evolutionary relationships among molecules, phenotypes, and organisms. In the context of protein sequence data, phylogenetic analysis is one of the cornerstones of comparative sequence analysis and has many applications in the study of protein evolution and function. This unit provides a brief review of the principles of phylogenetic analysis and describes several different standard phylogenetic analyses of protein sequence data using the RAXML (Randomized Axelerated Maximum Likelihood) Program. Curr. Protoc. Mol. Biol. 96:19.11.1-19.11.14. C 2011 by John Wiley & Sons, Inc. Keywords: molecular evolution r bootstrap r multiple sequence alignment r amino acid substitution matrix r evolutionary relationship r systematics INTRODUCTION the baboon-colobus monkey lineage almost Phylogenetic analysis is a standard and es- 25 million years ago, whereas baboons and sential tool in any molecular biologist’s bioin- colobus monkeys diverged less than 15 mil- formatics toolkit that, in the context of pro- lion years ago (Sterner et al., 2006). Clearly, tein sequence analysis, enables us to study degree of sequence similarity does not equate the evolutionary history and change of pro- with degree of evolutionary relationship. teins and their function. Such analysis is es- A typical phylogenetic analysis of protein sential to understanding major evolutionary sequence data involves five distinct steps: (a) questions, such as the origins and history of data collection, (b) inference of homology, (c) macromolecules, developmental mechanisms, sequence alignment, (d) alignment trimming, phenotypes, and life itself.