Protein Domains
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Gene Prediction: the End of the Beginning Comment Colin Semple
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by PubMed Central http://genomebiology.com/2000/1/2/reports/4012.1 Meeting report Gene prediction: the end of the beginning comment Colin Semple Address: Department of Medical Sciences, Molecular Medicine Centre, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK. E-mail: [email protected] Published: 28 July 2000 reviews Genome Biology 2000, 1(2):reports4012.1–4012.3 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2000/1/2/reports/4012 © GenomeBiology.com (Print ISSN 1465-6906; Online ISSN 1465-6914) Reducing genomes to genes reports A report from the conference entitled Genome Based Gene All ab initio gene prediction programs have to balance sensi- Structure Determination, Hinxton, UK, 1-2 June, 2000, tivity against accuracy. It is often only possible to detect all organised by the European Bioinformatics Institute (EBI). the real exons present in a sequence at the expense of detect- ing many false ones. Alternatively, one may accept only pre- dictions scoring above a more stringent threshold but lose The draft sequence of the human genome will become avail- those real exons that have lower scores. The trick is to try and able later this year. For some time now it has been accepted increase accuracy without any large loss of sensitivity; this deposited research that this will mark a beginning rather than an end. A vast can be done by comparing the prediction with additional, amount of work will remain to be done, from detailing independent evidence. -
Enhanced Representation of Natural Product Metabolism in Uniprotkb
H OH metabolites OH Article Diverse Taxonomies for Diverse Chemistries: Enhanced Representation of Natural Product Metabolism in UniProtKB Marc Feuermann 1,* , Emmanuel Boutet 1,* , Anne Morgat 1 , Kristian B. Axelsen 1, Parit Bansal 1, Jerven Bolleman 1 , Edouard de Castro 1, Elisabeth Coudert 1, Elisabeth Gasteiger 1,Sébastien Géhant 1, Damien Lieberherr 1, Thierry Lombardot 1,†, Teresa B. Neto 1, Ivo Pedruzzi 1, Sylvain Poux 1, Monica Pozzato 1, Nicole Redaschi 1 , Alan Bridge 1 and on behalf of the UniProt Consortium 1,2,3,4,‡ 1 Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, CMU, 1 Michel-Servet, CH-1211 Geneva 4, Switzerland; [email protected] (A.M.); [email protected] (K.B.A.); [email protected] (P.B.); [email protected] (J.B.); [email protected] (E.d.C.); [email protected] (E.C.); [email protected] (E.G.); [email protected] (S.G.); [email protected] (D.L.); [email protected] (T.L.); [email protected] (T.B.N.); [email protected] (I.P.); [email protected] (S.P.); [email protected] (M.P.); [email protected] (N.R.); [email protected] (A.B.); [email protected] (U.C.) 2 European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK 3 Protein Information Resource, University of Delaware, 15 Innovation Way, Suite 205, Newark, DE 19711, USA 4 Protein Information Resource, Georgetown University Medical Center, 3300 Whitehaven Street NorthWest, Suite 1200, Washington, DC 20007, USA * Correspondence: [email protected] (M.F.); [email protected] (E.B.); Tel.: +41-22-379-58-75 (M.F.); +41-22-379-49-10 (E.B.) † Current address: Centre Informatique, Division Calcul et Soutien à la Recherche, University of Lausanne, CH-1015 Lausanne, Switzerland. -
The EMBL-European Bioinformatics Institute the Hub for Bioinformatics in Europe
The EMBL-European Bioinformatics Institute The hub for bioinformatics in Europe Blaise T.F. Alako, PhD [email protected] www.ebi.ac.uk What is EMBL-EBI? • Part of the European Molecular Biology Laboratory • International, non-profit research institute • Europe’s hub for biological data, services and research The European Molecular Biology Laboratory Heidelberg Hamburg Hinxton, Cambridge Basic research Structural biology Bioinformatics Administration Grenoble Monterotondo, Rome EMBO EMBL staff: 1500 people Structural biology Mouse biology >60 nationalities EMBL member states Austria, Belgium, Croatia, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom Associate member state: Australia Who we are ~500 members of staff ~400 work in services & support >53 nationalities ~120 focus on basic research EMBL-EBI’s mission • Provide freely available data and bioinformatics services to all facets of the scientific community in ways that promote scientific progress • Contribute to the advancement of biology through basic investigator-driven research in bioinformatics • Provide advanced bioinformatics training to scientists at all levels, from PhD students to independent investigators • Help disseminate cutting-edge technologies to industry • Coordinate biological data provision throughout Europe Services Data and tools for molecular life science www.ebi.ac.uk/services Browse our services 9 What services do we provide? Labs around the -
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. -
Tunca Doğan , Alex Bateman , Maria J. Martin Your Choice
(—THIS SIDEBAR DOES NOT PRINT—) UniProt Domain Architecture Alignment: A New Approach for Protein Similarity QUICK START (cont.) DESIGN GUIDE Search using InterPro Domain Annotation How to change the template color theme This PowerPoint 2007 template produces a 44”x44” You can easily change the color theme of your poster by going to presentation poster. You can use it to create your research 1 1 1 the DESIGN menu, click on COLORS, and choose the color theme of poster and save valuable time placing titles, subtitles, text, Tunca Doğan , Alex Bateman , Maria J. Martin your choice. You can also create your own color theme. and graphics. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), We provide a series of online tutorials that will guide you Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK through the poster design process and answer your poster Correspondence: [email protected] production questions. To view our template tutorials, go online to PosterPresentations.com and click on HELP DESK. ABSTRACT METHODOLOGY RESULTS & DISCUSSION When you are ready to print your poster, go online to InterPro Domains, DAs and DA Alignment PosterPresentations.com Motivation: Similarity based methods have been widely used in order to Generation of the Domain Architectures: You can also manually change the color of your background by going to VIEW > SLIDE MASTER. After you finish working on the master be infer the properties of genes and gene products containing little or no 1) Collect the hits for each protein from InterPro. Domain annotation coverage Overlap domain hits problem in Need assistance? Call us at 1.510.649.3001 difference b/w domain databases: the InterPro database: sure to go to VIEW > NORMAL to continue working on your poster. -
Evolution and Function of Drososphila Melanogaster Cis-Regulatory Sequences
Evolution and Function of Drososphila melanogaster cis-regulatory Sequences By Aaron Hardin A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Molecular and Cell Biology in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Michael Eisen, Chair Professor Doris Bachtrog Professor Gary Karpen Professor Lior Pachter Fall 2013 Evolution and Function of Drososphila melanogaster cis-regulatory Sequences This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License 2013 by Aaron Hardin 1 Abstract Evolution and Function of Drososphila melanogaster cis-regulatory Sequences by Aaron Hardin Doctor of Philosophy in Molecular and Cell Biology University of California, Berkeley Professor Michael Eisen, Chair In this work, I describe my doctoral work studying the regulation of transcription with both computational and experimental methods on the natural genetic variation in a population. This works integrates an investigation of the consequences of polymorphisms at three stages of gene regulation in the developing fly embryo: the diversity at cis-regulatory modules, the integration of transcription factor binding into changes in chromatin state and the effects of these inputs on the final phenotype of embryonic gene expression. i I dedicate this dissertation to Mela Hardin who has been here for me at all times, even when we were apart. ii Contents List of Figures iv List of Tables vi Acknowledgments vii 1 Introduction1 2 Within Species Diversity in cis-Regulatory Modules6 2.1 Introduction....................................6 2.2 Results.......................................8 2.2.1 Genome wide diversity in transcription factor binding sites......8 2.2.2 Genome wide purifying selection on cis-regulatory modules......9 2.3 Discussion.....................................9 2.4 Methods for finding polymorphisms...................... -
Download Final Programme
Session Overview Saturday 17 September 2011 11:15 - 13:15 Arrival and Registration ATC Main Entrance 13:15 - 13:30 Welcome and Opening Remarks Klaus Tschira Auditorium 13:30 - 18:00 Session 1: Somatic Genetics I Chaired by David Tuveson and Ewan Birney Klaus Tschira Auditorium 18:00 - 19:00 Keynote Lecture: Lynda Chin Klaus Tschira Auditorium 19:00 - 20:30 Dinner ATC Canteen Sunday 18 September 2011 09:00 - 12:30 Session 2: Somatic Genetics II / Epigenetics Chaired by James R. Downing Klaus Tschira Auditorium 12:30 - 14:30 Poster Session I and Lunch ATC Foyer and Helix A 14:30 - 18:30 Session 3: Mouse Genetics Chaired by Lynda Chin Klaus Tschira Auditorium 18:30 - 23:00 Gala Dinner and Live Music ATC Canteen and ATC Rooftop Lounge Page 1 EMBO|EMBL Symposium: Cancer Genomics Monday 19 September 2011 09:00 - 13:00 Session 4: Computational Chaired by Peter Lichter Klaus Tschira Auditorium 13:00 - 15:00 Poster Session II and Lunch ATC Foyer and Helix A 15:00 - 16:00 Session 5: Somatic Genetics III Chaired by Andy Futreal Klaus Tschira Auditorium 16:00 - 17:00 Keynote Lecture: Michael Stratton Klaus Tschira Auditorium 17:00 - 17:15 Closing Remarks and Poster Prize Klaus Tschira Auditorium Page 2 Programme Saturday 17 September 2011 11:15 - 13:15 Arrival and Registration ATC Main Entrance 13:15 - 13:30 Welcome and Opening Remarks Klaus Tschira Auditorium 13:30 - 18:00 Session 1: Somatic Genetics I Chaired by David Tuveson and Ewan Birney Klaus Tschira Auditorium 13:30 - 14:00 Somatic genomic alterations in chronic lymphocytic 1 leukemia Elias -
Phenotype Inference in an Escherichia Coli Strain Panel
TOOLS AND RESOURCES Phenotype inference in an Escherichia coli strain panel Marco Galardini1, Alexandra Koumoutsi2, Lucia Herrera-Dominguez2, Juan Antonio Cordero Varela1, Anja Telzerow2, Omar Wagih1, Morgane Wartel2, Olivier Clermont3,4, Erick Denamur3,4,5, Athanasios Typas2*, Pedro Beltrao1* 1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL- EBI), Hinxton, United Kingdom; 2Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany; 3INSERM, IAME, UMR1137, Paris, France; 4Universite´ Paris Diderot, Paris, France; 5APHP, Hoˆpitaux Universitaires Paris Nord Val-de-Seine, Paris, France Abstract Understanding how genetic variation contributes to phenotypic differences is a fundamental question in biology. Combining high-throughput gene function assays with mechanistic models of the impact of genetic variants is a promising alternative to genome-wide association studies. Here we have assembled a large panel of 696 Escherichia coli strains, which we have genotyped and measured their phenotypic profile across 214 growth conditions. We integrated variant effect predictors to derive gene-level probabilities of loss of function for every gene across all strains. Finally, we combined these probabilities with information on conditional gene essentiality in the reference K-12 strain to compute the growth defects of each strain. Not only could we reliably predict these defects in up to 38% of tested conditions, but we could also directly identify the causal variants that were validated through complementation assays. Our work demonstrates the power of forward predictive models and the possibility of precision genetic interventions. DOI: https://doi.org/10.7554/eLife.31035.001 *For correspondence: [email protected] (AT); [email protected] (PB) Introduction Competing interests: The Understanding the genetic and molecular basis of phenotypic differences among individuals is a authors declare that no long-standing problem in biology. -
Molecular Genetics & Genomics
page 46 Lab Times 5-2010 Ranking Illustration: Christina Ullman Publication Analysis 1997-2008 Molecular Genetics & Genomics Under the premise of a “narrow” definition of the field, Germany and England co-dominated European molecular genetics/genomics. The most frequently citated sub-fields were bioinformatical genomics, epigenetics, RNA biology and DNA repair. irst of all, a little science history (you’ll soon see why). As and expression. That’s where so-called computational biology is well known, in the 1950s genetics went molecular – and and systems biology enter research into basic genetic problems. Fdid not just become molecular genetics but rather molec- Given that development, it is not easy to answer the question ular bio logy. In 1963, however, Sydney Brenner wrote in his fa- what “molecular genetics & genomics” today actually is – and, mous letter to Max Perutz: “[...] I have long felt that the future of in particular, what is it in the context of our publication analy- molecular biology lies in the extension of research to other fields sis of the field? It is obvious that, as for example science historian of biology, notably development and the nervous system.” He Robert Olby put it, a “wide” definition can be distinguished from appeared not to be alone with this view and, as a consequence, a “narrow” definition of the field. The wide definition includes along with Brenner many of the leading molecular biologists all fields, into which molecular biology has entered as an exper- from the classical period redirected their research agendas, utilis- imental and theoretical paradigm. The “narrow” definition, on ing the newly developed molecular techniques to investigate un- the other hand, still tries to maintain the status as an explicit bio- solved problems in other fields. -
Pfam: the Protein Families Database in 2021 Jaina Mistry 1,*, Sara Chuguransky 1, Lowri Williams 1, Matloob Qureshi 1, Gustavo A
D412–D419 Nucleic Acids Research, 2021, Vol. 49, Database issue Published online 30 October 2020 doi: 10.1093/nar/gkaa913 Pfam: The protein families database in 2021 Jaina Mistry 1,*, Sara Chuguransky 1, Lowri Williams 1, Matloob Qureshi 1, Gustavo A. Salazar1, Erik L.L. Sonnhammer2, Silvio C.E. Tosatto 3, Lisanna Paladin 3, Shriya Raj 1, Lorna J. Richardson 1, Robert D. Finn 1 and Alex Bateman 1 1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK, 2Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden and 3Department of Biomedical Sciences, University of Padua, 35131 Padova, Italy Received September 11, 2020; Revised October 01, 2020; Editorial Decision October 02, 2020; Accepted October 06, 2020 ABSTRACT per-family gathering thresholds. Pfam entries are manually annotated with functional information from the literature The Pfam database is a widely used resource for clas- where available. sifying protein sequences into families and domains. Since Pfam release 29.0, pfamseq is based on UniPro- Since Pfam was last described in this journal, over tKB reference proteomes, whilst prior to that, it was based 350 new families have been added in Pfam 33.1 and on the whole of UniProtKB (3,4). Although the underly- numerous improvements have been made to existing ing sequence database is based on reference proteomes, all entries. To facilitate research on COVID-19, we have of the profile HMMs are also searched against UniProtKB revised the Pfam entries that cover the SARS-CoV-2 and the resulting matches are made available on the Pfam proteome, and built new entries for regions that were website and in a flatfile format. -
Rapid Identification of Novel Protein Families Using Similarity Searches [Version 1; Peer Review: 2 Approved]
F1000Research 2018, 7:1975 Last updated: 26 JUL 2021 METHOD ARTICLE Rapid identification of novel protein families using similarity searches [version 1; peer review: 2 approved] Matt Jeffryes, Alex Bateman European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, CB10 1SD, UK v1 First published: 24 Dec 2018, 7:1975 Open Peer Review https://doi.org/10.12688/f1000research.17315.1 Latest published: 24 Dec 2018, 7:1975 https://doi.org/10.12688/f1000research.17315.1 Reviewer Status Invited Reviewers Abstract Protein family databases are an important tool for biologists trying to 1 2 dissect the function of proteins. Comparing potential new families to the thousands of existing entries is an important task when operating version 1 a protein family database. This comparison helps to understand 24 Dec 2018 report report whether a collection of protein regions forms a novel family or has overlaps with existing families of proteins. In this paper, we describe a 1. Daniel J. Rigden , University of Liverpool, method for performing this analysis with an adjustable level of accuracy, depending on the desired speed, enabling interactive Liverpool, UK comparisons. This method is based upon the MinHash algorithm, 2. Desmond G Higgins, Conway Institute, which we have further extended to calculate the Jaccard containment rather than the Jaccard index of the original MinHash technique. University College Dublin, Dublin, Ireland Testing this method with the Pfam protein family database, we are able to compare potential new families to the over 17,000 existing Any reports and responses or comments on the families in Pfam in less than a second, with little loss in accuracy. -
Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by Pickeringhutchins Ltd
European Bioinformatics Institute EMBL-EBI Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by PickeringHutchins Ltd www.pickeringhutchins.com EMBL member states: Austria, Croatia, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom. Associate member state: Australia EMBL-EBI is a part of the European Molecular Biology Laboratory (EMBL) EMBL-EBI EMBL-EBI EMBL-EBI EMBL-European Bioinformatics Institute Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD United Kingdom Tel. +44 (0)1223 494 444, Fax +44 (0)1223 494 468 www.ebi.ac.uk EMBL Heidelberg Meyerhofstraße 1 69117 Heidelberg Germany Tel. +49 (0)6221 3870, Fax +49 (0)6221 387 8306 www.embl.org [email protected] EMBL Grenoble 6, rue Jules Horowitz, BP181 38042 Grenoble, Cedex 9 France Tel. +33 (0)476 20 7269, Fax +33 (0)476 20 2199 EMBL Hamburg c/o DESY Notkestraße 85 22603 Hamburg Germany Tel. +49 (0)4089 902 110, Fax +49 (0)4089 902 149 EMBL Monterotondo Adriano Buzzati-Traverso Campus Via Ramarini, 32 00015 Monterotondo (Rome) Italy Tel. +39 (0)6900 91402, Fax +39 (0)6900 91406 © 2012 EMBL-European Bioinformatics Institute All texts written by EBI-EMBL Group and Team Leaders. This publication was produced by the EBI’s Outreach and Training Programme. Contents Introduction Foreword 2 Major Achievements 2011 4 Services Rolf Apweiler and Ewan Birney: Protein and nucleotide data 10 Guy Cochrane: The European Nucleotide Archive 14 Paul Flicek: