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Easybuild Documentation Release 20210907.0
EasyBuild Documentation Release 20210907.0 Ghent University Tue, 07 Sep 2021 08:55:41 Contents 1 What is EasyBuild? 3 2 Concepts and terminology 5 2.1 EasyBuild framework..........................................5 2.2 Easyblocks................................................6 2.3 Toolchains................................................7 2.3.1 system toolchain.......................................7 2.3.2 dummy toolchain (DEPRECATED) ..............................7 2.3.3 Common toolchains.......................................7 2.4 Easyconfig files..............................................7 2.5 Extensions................................................8 3 Typical workflow example: building and installing WRF9 3.1 Searching for available easyconfigs files.................................9 3.2 Getting an overview of planned installations.............................. 10 3.3 Installing a software stack........................................ 11 4 Getting started 13 4.1 Installing EasyBuild........................................... 13 4.1.1 Requirements.......................................... 14 4.1.2 Using pip to Install EasyBuild................................. 14 4.1.3 Installing EasyBuild with EasyBuild.............................. 17 4.1.4 Dependencies.......................................... 19 4.1.5 Sources............................................. 21 4.1.6 In case of installation issues. .................................. 22 4.2 Configuring EasyBuild.......................................... 22 4.2.1 Supported configuration -
Retrovirus-Like Elements in Plants
Research Signpost 37/661 (2), Fort P.O., Trivandrum-695 023, Kerala, India Recent Res. Devel. Plant Sci., 3(2005): ISBN: 81-7736-245-3 Retrovirus-like elements in plants Antonio Marco and Ignacio Marín Departamento de Genética, Universidad de Valencia, Calle Doctor Moliner, 50 46100 Burjassot (Valencia), Spain Abstract LTR retrotransposons with structures that are identical to those found in simple vertebrate retroviruses, including a putative env gene, have been discovered in plants. Those potential plant retroviruses can be classified into two classes. The first one is formed by the Arabidopsis thaliana Athila elements and many other closely related env- containing elements. All of them belong to the Ty3/Gypsy group of LTR retrotransposons. The second class, in which the best-known element was first found in soybean and called SIRE1, belongs to the Ty1/Copia group. Thus, two distantly related lineages have convergent features that suggest that the transition between intracellular and infective ways of life may have occurred several times independently. Correspondence/Reprint request: Dr. Ignacio Marín, Departamento de Genética, Universidad de Valencia Calle Doctor Moliner, 50, 46100 Burjassot (Valencia), Spain. E-mail: [email protected] 2 Antonio Marco & Ignacio Marín Introduction First discovered in maize by Barbara McClintock and later recognized in all types of organisms, transposable elements are ubiquitous components of plant genomes. Eukaryotic transposable elements are generally divided into two classes. Class II elements or DNA transposons do not require an intermediate RNA. Class I elements however, require an intermediate RNA and cannot complete its replicative cycle without the use of the enzyme reverse transcriptase (RT), able to generate DNA molecules from RNA templates. -
2007Murciaphd.Pdf
https://theses.gla.ac.uk/ Theses Digitisation: https://www.gla.ac.uk/myglasgow/research/enlighten/theses/digitisation/ This is a digitised version of the original print thesis. Copyright and moral rights for this work are retained by the author A copy can be downloaded for personal non-commercial research or study, without prior permission or charge This work cannot be reproduced or quoted extensively from without first obtaining permission in writing from the author The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given Enlighten: Theses https://theses.gla.ac.uk/ [email protected] LATE RESTRICTION INDUCED BY AN ENDOGENOUS RETROVIRUS Pablo Ramiro Murcia August 2007 Thesis presented to the School of Veterinary Medicine at the University of Glasgow for the degree of Doctor of Philosophy Institute of Comparative Medicine 464 Bearsden Road Glasgow G61 IQH ©Pablo Murcia ProQuest Number: 10390741 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. uest ProQuest 10390741 Published by ProQuest LLO (2017). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code Microform Edition © ProQuest LLO. -
Bioperl What’S Bioperl?
Bioperl What’s Bioperl? Bioperl is not a new language It is a collection of Perl modules that facilitate the development of Perl scripts for bioinformatics applications. Bioperl and perl Bioperl Modules Perl Modules Perls script input Perl Interpreter output Bioperl and Perl Why bioperl for bioinformatics? Perl is good at file manipulation and text processing, which make up a large part of the routine tasks in bioinformatics. Perl language, documentation and many Perl packages are freely available. Perl is easy to get started in, to write small and medium-sized programs. Where to get help Type perldoc <modulename> in terminal Search for particular module in https://metacpan.org Bioperl Document Object-oriented and Process-oriented programming Process-oriented: Yuan Hao eats chicken Name object: $name Action method: eat Food object: $food Object-oriented: $name->eat($food) Modularize the program Platform and Related Software Required Perl 5.6.1 or higher Version 5.8 or higher is highly recommended make for Mac OS X, this requires installing the Xcode Developer Tools Installation On Linux or Max OS X Install from cpanminus: perlbrew install-cpanm cpanm Bio::Perl Install from source code: git clone https://github.com/bioperl/bioperl-live.git cd bioperl-live perl Build.PL ./Build test (optional) ./Build install Installation On Windows Install MinGW (MinGW is incorporated in Strawberry Perl, but must it be installed through PPM for ActivePerl) : ppm install MinGW Install Module::Build, Test::Harness and Test::Most through CPAN: Type cpan to enter the CPAN shell. At the cpan> prompt, type install CPAN Quit (by typing ‘q’) and reload CPAN. -
The Bioperl Toolkit: Perl Modules for the Life Sciences
Downloaded from genome.cshlp.org on January 25, 2012 - Published by Cold Spring Harbor Laboratory Press The Bioperl Toolkit: Perl Modules for the Life Sciences Jason E. Stajich, David Block, Kris Boulez, et al. Genome Res. 2002 12: 1611-1618 Access the most recent version at doi:10.1101/gr.361602 Supplemental http://genome.cshlp.org/content/suppl/2002/10/20/12.10.1611.DC1.html Material References This article cites 14 articles, 9 of which can be accessed free at: http://genome.cshlp.org/content/12/10/1611.full.html#ref-list-1 Article cited in: http://genome.cshlp.org/content/12/10/1611.full.html#related-urls Email alerting Receive free email alerts when new articles cite this article - sign up in the box at the service top right corner of the article or click here To subscribe to Genome Research go to: http://genome.cshlp.org/subscriptions Cold Spring Harbor Laboratory Press Downloaded from genome.cshlp.org on January 25, 2012 - Published by Cold Spring Harbor Laboratory Press Resource The Bioperl Toolkit: Perl Modules for the Life Sciences Jason E. Stajich,1,18,19 David Block,2,18 Kris Boulez,3 Steven E. Brenner,4 Stephen A. Chervitz,5 Chris Dagdigian,6 Georg Fuellen,7 James G.R. Gilbert,8 Ian Korf,9 Hilmar Lapp,10 Heikki Lehva¨slaiho,11 Chad Matsalla,12 Chris J. Mungall,13 Brian I. Osborne,14 Matthew R. Pocock,8 Peter Schattner,15 Martin Senger,11 Lincoln D. Stein,16 Elia Stupka,17 Mark D. Wilkinson,2 and Ewan Birney11 1University Program in Genetics, Duke University, Durham, North Carolina 27710, USA; 2National Research Council of -
Geve: a Genome-Based Endogenous Viral Element Database Provides
Database, 2016, 1–8 doi: 10.1093/database/baw087 Original article Original article Downloaded from https://academic.oup.com/database/article-abstract/doi/10.1093/database/baw087/2630466 by guest on 24 July 2019 gEVE: a genome-based endogenous viral element database provides comprehensive viral protein-coding sequences in mammalian genomes So Nakagawa1,2,* and Mahoko Ueda Takahashi2 1Department of Molecular Life Science, Tokai University School of Medicine, 143 Shimokasuya, Isehara, Kanagawa 259-1193, Japan and 2Micro/Nano Technology Center, Tokai University, 411 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan *Corresponding author: Tel: þ81 463 93 1121 ext. 2661; Fax: þ81 463 93 5418; Email: [email protected] Citation details: Nakagawa,S. and Ueda Takahashi,M. gEVE: a genome-based endogenous viral element database pro- vides comprehensive viral protein-coding sequences in mammalian genomes. Database (2016) Vol. 2016: article ID baw087; doi:10.1093/database/baw087 Received 15 December 2015; Revised 15 April 2016; Accepted 4 May 2016 Abstract In mammals, approximately 10% of genome sequences correspond to endogenous viral elements (EVEs), which are derived from ancient viral infections of germ cells. Although most EVEs have been inactivated, some open reading frames (ORFs) of EVEs obtained functions in the hosts. However, EVE ORFs usually remain unannotated in the genomes, and no databases are available for EVE ORFs. To investigate the function and evolution of EVEs in mammalian genomes, we developed EVE ORF databases for 20 genomes of 19 mammalian species. A total of 736,771 non-overlapping EVE ORFs were identified and archived in a database named gEVE (http://geve.med.u-tokai.ac.jp). -
Diversity of Large DNA Viruses of Invertebrates ⇑ Trevor Williams A, Max Bergoin B, Monique M
Journal of Invertebrate Pathology 147 (2017) 4–22 Contents lists available at ScienceDirect Journal of Invertebrate Pathology journal homepage: www.elsevier.com/locate/jip Diversity of large DNA viruses of invertebrates ⇑ Trevor Williams a, Max Bergoin b, Monique M. van Oers c, a Instituto de Ecología AC, Xalapa, Veracruz 91070, Mexico b Laboratoire de Pathologie Comparée, Faculté des Sciences, Université Montpellier, Place Eugène Bataillon, 34095 Montpellier, France c Laboratory of Virology, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands article info abstract Article history: In this review we provide an overview of the diversity of large DNA viruses known to be pathogenic for Received 22 June 2016 invertebrates. We present their taxonomical classification and describe the evolutionary relationships Revised 3 August 2016 among various groups of invertebrate-infecting viruses. We also indicate the relationships of the Accepted 4 August 2016 invertebrate viruses to viruses infecting mammals or other vertebrates. The shared characteristics of Available online 31 August 2016 the viruses within the various families are described, including the structure of the virus particle, genome properties, and gene expression strategies. Finally, we explain the transmission and mode of infection of Keywords: the most important viruses in these families and indicate, which orders of invertebrates are susceptible to Entomopoxvirus these pathogens. Iridovirus Ó Ascovirus 2016 Elsevier Inc. All rights reserved. Nudivirus Hytrosavirus Filamentous viruses of hymenopterans Mollusk-infecting herpesviruses 1. Introduction in the cytoplasm. This group comprises viruses in the families Poxviridae (subfamily Entomopoxvirinae) and Iridoviridae. The Invertebrate DNA viruses span several virus families, some of viruses in the family Ascoviridae are also discussed as part of which also include members that infect vertebrates, whereas other this group as their replication starts in the nucleus, which families are restricted to invertebrates. -
Genomic Neighborhoods for Arabidopsisretrotransposons: a Role for Targeted Integration in the Distribution of the Metaviridae Brooke D
Statistics Publications Statistics 2004 Genomic neighborhoods for Arabidopsisretrotransposons: a role for targeted integration in the distribution of the Metaviridae Brooke D. Peterson-Burch U.S. Department of Agriculture Dan Nettleton Iowa State University, [email protected] Daniel F. Voytas Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/stat_las_pubs Part of the Applied Statistics Commons, Cell and Developmental Biology Commons, Genetics and Genomics Commons, and the Statistical Models Commons The ompc lete bibliographic information for this item can be found at https://lib.dr.iastate.edu/ stat_las_pubs/228. For information on how to cite this item, please visit http://lib.dr.iastate.edu/ howtocite.html. This Article is brought to you for free and open access by the Statistics at Iowa State University Digital Repository. It has been accepted for inclusion in Statistics Publications by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Genomic neighborhoods for Arabidopsisretrotransposons: a role for targeted integration in the distribution of the Metaviridae Abstract Background: Retrotransposons are an abundant component of eukaryotic genomes. The high quality of the Arabidopsis thaliana genome sequence makes it possible to comprehensively characterize retroelement populations and explore factors that contribute to their genomic distribution. Results: We identified the full complement of A. thaliana long terminal repeat (LTR) retroelements using RetroMap, a software tool that iteratively searches genome sequences for reverse transcriptases and then defines retroelement insertions. Relative ages of full-length elements were estimated by assessing sequence divergence between LTRs: the Pseudoviridae were significantly younger than the Metaviridae. -
Virus World As an Evolutionary Network of Viruses and Capsidless Selfish Elements
Virus World as an Evolutionary Network of Viruses and Capsidless Selfish Elements Koonin, E. V., & Dolja, V. V. (2014). Virus World as an Evolutionary Network of Viruses and Capsidless Selfish Elements. Microbiology and Molecular Biology Reviews, 78(2), 278-303. doi:10.1128/MMBR.00049-13 10.1128/MMBR.00049-13 American Society for Microbiology Version of Record http://cdss.library.oregonstate.edu/sa-termsofuse Virus World as an Evolutionary Network of Viruses and Capsidless Selfish Elements Eugene V. Koonin,a Valerian V. Doljab National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland, USAa; Department of Botany and Plant Pathology and Center for Genome Research and Biocomputing, Oregon State University, Corvallis, Oregon, USAb Downloaded from SUMMARY ..................................................................................................................................................278 INTRODUCTION ............................................................................................................................................278 PREVALENCE OF REPLICATION SYSTEM COMPONENTS COMPARED TO CAPSID PROTEINS AMONG VIRUS HALLMARK GENES.......................279 CLASSIFICATION OF VIRUSES BY REPLICATION-EXPRESSION STRATEGY: TYPICAL VIRUSES AND CAPSIDLESS FORMS ................................279 EVOLUTIONARY RELATIONSHIPS BETWEEN VIRUSES AND CAPSIDLESS VIRUS-LIKE GENETIC ELEMENTS ..............................................280 Capsidless Derivatives of Positive-Strand RNA Viruses....................................................................................................280 -
Vasco Da Rocha Figueiras Algoritmos Para Genómica Comparativa
Universidade de Aveiro Departamento Electrónica, Telecomunicações 2010 e Informática Vasco da Rocha Algoritmos para Genómica Comparativa Figueiras Universidade de Aveiro Departamento de Electrónica, Telecomunicações 2010 e Informática Vasco da Rocha Algoritmos para Genómica Comparativa Figueiras Dissertação apresentada à Universidade de Aveiro para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Engenharia Electrónica e Telecomunicações, realizada sob a orientação científica do Doutor José Luís Oliveira, Professor associado da Universidade de Aveiro. o júri presidente Prof. Doutor Armando José Formoso de Pinho Professor Associado do Departamento de Electrónica, Telecomunicações e Informática da Universidade de Aveiro Prof. Doutor Rui Pedro Sanches de Castro Lopes Professor Coodenador do Departamento de Informática e Comunicações do Instituto Politécnico de Bragança orientador Prof. Doutor José Luis Guimarães de Oliveira Professor Associado do Departamento de Electrónica, Telecomunicações e Informática da Universidade de Aveiro agradecimentos Durante o desenvolvimento desta dissertação, recebi muito apoio de colegas e amigos. Agora que termino o trabalho não posso perder a oportunidade de agradecer a todas as pessoas que me ajudaram nesta etapa. Um agradecimento ao meu orientador Professor Doutor José Luís Oliveira e ao Doutor Miguel Monsanto Pinheiro, pela oportunidade de aprendizagem. À minha família pelo apoio incondicional, incentivo e carinho. Aos meus colegas e amigos por toda a ajuda e pelos momentos de convívio e de descontracção, que quebraram tantas dificuldades, ao longo desta etapa. A ti, Rita por todo o carinho, paciência e amor. palavras-chave Bioinformática, sequenciação, BLAST, alinhamento de sequências, genómica comparativa. resumo Com o surgimento da Genómica e da Proteómica, a Bioinformática conduziu a alguns dos avanços científicos mais relevantes do século XX. -
Perl for Bioinformatics Perl and Bioperl I
Perl for Bioinformatics Perl and BioPerl I Jason Stajich July 13, 2011 Perl for Bioinformatics Slide 1/83 Outline Perl Intro Basics Syntax and Variables More complex: References Routines Reading and Writing Regular Expressions BioPerl Intro Useful modules Data formats Databases in BioPerl Sequence objects details Trees Multiple Alignments BLAST and Sequence Database searching Other general Perl modules Perl for Bioinformatics Perl Intro Slide 2/83 Outline Perl Intro Basics Syntax and Variables More complex: References Routines Reading and Writing Regular Expressions BioPerl Intro Useful modules Data formats Databases in BioPerl Sequence objects details Trees Multiple Alignments BLAST and Sequence Database searching Other general Perl modules Perl for Bioinformatics Perl Intro Basics Slide 3/83 Why Perl for data processing & bioinformatics Fast text processing Regular expressions Extensive module libraries for pre-written tools Large number of users in community of bioinformatics Scripts are often faster to write than full compiled programs Cons Syntax sometimes confusing to new users; 'There's more than one way to do it' can also be confusing. (TMTOWTDI) Cons Not a true object-oriented language so some abstraction is clunky and hacky Scripting languages (Perl, Python, Ruby) generally easier to write simply than compiled ones (C, C++, Java) as they are often not strongly typed and less memory management control. Perl for Bioinformatics Perl Intro Basics Slide 4/83 Perl packages CPAN - Comprehensive Perl Archive http://www.cpan.org Perl -
RNA Viruses of Amblyomma Variegatum and Rhipicephalus Microplus and Cattle Susceptibility in the French Antilles
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 12 December 2019 doi:10.20944/preprints201912.0172.v1 Peer-reviewed version available at Viruses 2020, 12, 144; doi:10.3390/v12020144 Article RNA viruses of Amblyomma variegatum and Rhipicephalus microplus and cattle susceptibility in the French Antilles Mathilde Gondard 1,2,#, Sarah Temmam 3,#, Elodie Devillers 1, Valérie Pinarello 2,4, Thomas Bigot 3,5, Delphine Chrétien 3, Rosalie Aprelon 2,4, Muriel Vayssier-Taussat 1, Emmanuel Albina 2,4, Marc Eloit 3,6* and Sara Moutailler 1* 1 UMR BIPAR, Animal Health Laboratory, ANSES, INRA, Ecole Nationale Vétérinaire d’Alfort, Université Paris-Est, Maisons-Alfort, France; [email protected]; [email protected]; [email protected]; [email protected] 2 CIRAD, UMR ASTRE, F-97170 Petit-Bourg, Guadeloupe, France; [email protected]; [email protected]; [email protected] 3 Institut Pasteur, Biology of Infection Unit, Inserm U1117, Pathogen Discovery Laboratory, Paris, France; [email protected] ; [email protected] ; [email protected] ; [email protected] 4 ASTRE, Univ Montpellier, CIRAD, INRA, Montpellier, France; [email protected]; [email protected]; [email protected] 5 Institut Pasteur – Bioinformatics and Biostatistics Hub – Computational Biology Department, Institut Pasteur, USR 3756 CNRS, Paris, France. 6 National Veterinary School of Alfort, Paris-Est University, Maisons-Alfort, 94704 Cedex, France. [email protected] # These authors contributed equally. * Correspondence: [email protected]; Tel.: +33 1 49 77 46 50; [email protected]; Tel.: +33 1 44 38 92 16 Abstract: Ticks transmit a wide variety of pathogens including bacteria, parasites and viruses.