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Bioinformatics: a Practical Guide to the Analysis of Genes and Proteins, Second Edition Andreas D
BIOINFORMATICS A Practical Guide to the Analysis of Genes and Proteins SECOND EDITION Andreas D. Baxevanis Genome Technology Branch National Human Genome Research Institute National Institutes of Health Bethesda, Maryland USA B. F. Francis Ouellette Centre for Molecular Medicine and Therapeutics Children’s and Women’s Health Centre of British Columbia University of British Columbia Vancouver, British Columbia Canada A JOHN WILEY & SONS, INC., PUBLICATION New York • Chichester • Weinheim • Brisbane • Singapore • Toronto BIOINFORMATICS SECOND EDITION METHODS OF BIOCHEMICAL ANALYSIS Volume 43 BIOINFORMATICS A Practical Guide to the Analysis of Genes and Proteins SECOND EDITION Andreas D. Baxevanis Genome Technology Branch National Human Genome Research Institute National Institutes of Health Bethesda, Maryland USA B. F. Francis Ouellette Centre for Molecular Medicine and Therapeutics Children’s and Women’s Health Centre of British Columbia University of British Columbia Vancouver, British Columbia Canada A JOHN WILEY & SONS, INC., PUBLICATION New York • Chichester • Weinheim • Brisbane • Singapore • Toronto Designations used by companies to distinguish their products are often claimed as trademarks. In all instances where John Wiley & Sons, Inc., is aware of a claim, the product names appear in initial capital or ALL CAPITAL LETTERS. Readers, however, should contact the appropriate companies for more complete information regarding trademarks and registration. Copyright ᭧ 2001 by John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic or mechanical, including uploading, downloading, printing, decompiling, recording or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. -
Keynote Speaker
4th BSC Severo Ochoa Doctoral Symposium KEYNOTE SPEAKER Alfonso Valencia Head of Life Sciences Department, BSC Personalised Medicine as a Computational Challenge Personalized Medicine represents the adoption of Genomics and other –omics technologies to the diagnosis and treatment of diseases. PerMed is one of the more interesting and promising developments resulting from the genomic revolution. The treatment and analysis of genomic information is tremendously challenging for a number of reasons that include the diversity and heterogeneity of the data, strong dependence of the associated metadata (i.e, experimental details), very fast evolution of the methods, and the size and confidentiality of the data sets. Furthermore, the lack of a sufficiently developed conceptual framework in Molecular Biology makes the interpretation of the data extremely difficult. In parallel, the work in human diseases will require the combination of the –omics information with the description of diseases, symptoms, drugs and treatments: The use of this information, recorded in Electronic Medical Records and other associated documents, requires the development and application of Text Mining and Natural Language processing technologies. These problems have to be seen as opportunities, particularly for students and Post Docs in Bioinformatics, Engineering and Computer Sciences. During this talk, I will introduce some of the areas in which the Life Sciences Department works, from Simulation to Genome Analysis, including text mining, pointing to what I see as the most promising future areas of development. Alfonso Valencia is the founder and President of the International Society for Computational Biology and Co-Executive Director of the main journal in the field (Bioinformatics of Oxford University Press). -
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: -
PLOS Computational Biology Associate Editor Handbook Second Edition Version 2.6
PLOS Computational Biology Associate Editor Handbook Second Edition Version 2.6 Welcome and thank you for your support of PLOS Computational Biology and the Open Access movement. PLOS Computational Biology is one of the four community run, Open Access journals published by the Public Library of Science. The journal features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Since its launch in 2005, PLOS Computational Biology has grown not only in the number of papers published, but also in recognition as a quality publication and community resource. We have every reason to expect that this trend will continue and our team of Associate Editors play an invaluable role in this process. Associate Editors oversee the peer review process for the journal, including evaluating submissions, selecting reviewers, assessing reviewer comments, and making editorial decisions. Together with fellow Editorial Board members and the PLOS CB Team, Associate Editors uphold journal policies and ethical standards and work to promote the PLOS mission to provide free public access to scientific research. PLOS Computational Biology is one of a suite of influential journals published by PLOS. Information about the other journals, the PLOS business model, PLOS innovations in scientific publishing, and Open Access copyright and licensure can be found in Appendix IX. Table of Contents PLOS Computational Biology Editorial Board Membership ................................................................................... 2 Manuscript Evaluation ..................................................................................................................................... -
A Comprehensive and Quantitative Comparison of Text-Mining in 15 Million Full-Text Articles Versus Their Corresponding Abstracts
A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts Westergaard, David; Stærfeldt, Hans-Henrik; Tønsberg, Christian; Jensen, Lars Juhl; Brunak, Søren Published in: PLoS Computational Biology DOI: 10.1371/journal.pcbi.1005962 Publication date: 2018 Document version Publisher's PDF, also known as Version of record Document license: CC BY Citation for published version (APA): Westergaard, D., Stærfeldt, H-H., Tønsberg, C., Jensen, L. J., & Brunak, S. (2018). A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts. PLoS Computational Biology, 14(2), [e1005962]. https://doi.org/10.1371/journal.pcbi.1005962 Download date: 08. Apr. 2020 RESEARCH ARTICLE A comprehensive and quantitative comparison of text-mining in 15 million full- text articles versus their corresponding abstracts David Westergaard1,2, Hans-Henrik Stñrfeldt1, Christian Tønsberg3, Lars Juhl Jensen2*, Søren Brunak1* 1 Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of a1111111111 Denmark, Lyngby, Denmark, 2 Novo Nordisk Foundation Center for Protein Research, Faculty of Health and a1111111111 Medical Sciences, University of Copenhagen, Copenhagen, Denmark, 3 Office for Innovation and Sector a1111111111 Services, Technical Information Center of Denmark, Technical University of Denmark, Lyngby, Denmark a1111111111 * [email protected] (LJJ); [email protected] (SB) a1111111111 Abstract OPEN ACCESS Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has Citation: Westergaard D, Stñrfeldt H-H, Tønsberg C, Jensen LJ, Brunak S (2018) A comprehensive mostly been carried out on collections of abstracts, due to their availability. -
Self-Archiving in Practice: What Do the Researchers Say and Is There Any Pain Alleviation?
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Göteborgs universitets publikationer - e-publicering och e-arkiv SELF-ARCHIVING IN PRACTICE: WHAT DO THE RESEARCHERS SAY AND IS THERE ANY PAIN ALLEVIATION? Peter Linde1; Carin Björklund2; Jörgen Eriksson3; Aina Svensson4. 1Blekinge Institute of Technology 371 79 Karlskrona e-mail: [email protected] 2 University of Gothenburg Box 222, 405 30 Gothenburg e-mail: [email protected] 3Lund University Box 117, 221 00 Lund e-mail: [email protected] 4Uppsala University Box 256, 751 05 Uppsala e-mail: [email protected] Abstract The purpose of the study was to increase self-archiving of scientific articles in Swedish open archives and thus contribute to the dissemination and increased visibility of Swedish research and to a greater impact for the individual researcher. We wanted to find out what obstacles may occur in the self-archiving process and how the database SHERPA/RoMEO functions as support for control of the pub- lishers’ conditions. We engaged 40 researchers at 7 Swedish institutes of higher education to self-archive their peer-reviewed journal articles from the last 5 years. The result was that 140 publications were self-archived in the open archives of these universities and university colleges. After the self-archiving was carried out we followed up on the researchers’ experiences and viewpoints in the form of oral interviews. We have found several imperfections and problems in the process of self-archiving. These issues are discussed and then we conclude with suggestions for measures to take, which we believe are crucial to making self-archiving gener- ally accepted in the world of research and therefore increasing the dissemination of research results. -
Bioinformatics Is a New Discipline That Addresses the Need to Manage and Interpret the Data That in the Past Decade Was Massively Generated by Genomic Research
SABU M. THAMPI Assistant Professor Dept. of CSE LBS College of Engineering Kasaragod, Kerala-671542 [email protected] Introduction Bioinformatics is a new discipline that addresses the need to manage and interpret the data that in the past decade was massively generated by genomic research. This discipline represents the convergence of genomics, biotechnology and information technology, and encompasses analysis and interpretation of data, modeling of biological phenomena, and development of algorithms and statistics. Bioinformatics is by nature a cross-disciplinary field that began in the 1960s with the efforts of Margaret O. Dayhoff, Walter M. Fitch, Russell F. Doolittle and others and has matured into a fully developed discipline. However, bioinformatics is wide-encompassing and is therefore difficult to define. For many, including myself, it is still a nebulous term that encompasses molecular evolution, biological modeling, biophysics, and systems biology. For others, it is plainly computational science applied to a biological system. Bioinformatics is also a thriving field that is currently in the forefront of science and technology. Our society is investing heavily in the acquisition, transfer and exploitation of data and bioinformatics is at the center stage of activities that focus on the living world. It is currently a hot commodity, and students in bioinformatics will benefit from employment demand in government, the private sector, and academia. With the advent of computers, humans have become ‘data gatherers’, measuring every aspect of our life with inferences derived from these activities. In this new culture, everything can and will become data (from internet traffic and consumer taste to the mapping of galaxies or human behavior). -
Alfonso Valencia
Alfonso Valencia Vice Chair of the IMI Scientific Committee Life Sciences Department Director / BSC – Barcelona Supercomputing Center ICREA Research Professor Head of the Spanish node of ELIXIR Director / Spanish National Bioinformatics Institute Alfonso Valencia is a Biologist by training with a Ph.D. in Biochemistry and Molecular Biology by the Universidad Autónoma, Madrid. Alfonso Valencia has published more than 300 articles with an h-index of 94 (Google Scholar profile). His group participates in various international consortiums including GENCODE/ENCODE, BLUEPRINT/IHEC (epigenomics), RD-Connect/IRDiRC (rare diseases), CLL/ICGC/PCAWG (cancer genomics) and OpenMinted (e-infrastructure in text mining). Alfonso Valencia is a founder and current member of the steering committee of the BioCreative Text Mining challenge, where he has emphasized particularly the importance of text mining in the connection between Molecular Biology and Chemistry. Prof. Valencia is a founder member and current President of the International Society for Computational Biology (ISCB), elected member of the European Molecular Biology Organization (EMBO). Prof. Valencia is Executive Editor of the main journal in the field since 2006 (“Bioinformatics” OUP) and editors of FEBS Letters, PeerJ and F1000Prime. He is also reviewing Editor of e-LIFE. Prof. Valencia is or has been member of a number of advisor boards, including EMBL, BioZentrum U. Basel, Swiss Bioinformatics Institute, EMBL- EBI chemical and protein domain databases, Department of Biology UPF, Department of Bioinformatics Curie Institute, IRB-Barcelona, among others. Dr. Valencia is Professor Honoris Causa by the Danish Technical University - DTU. Previous positions . Vice Director basic Research, CNIO – Spanish National Cancer Research Center, 2014-2017 . -
Journal of Integrative Bioinformatics 2020; 17(2–3): 20200006
Journal of Integrative Bioinformatics 2020; 17(2–3): 20200006 Workshop Søren Brunak, Catherine Bjerre Collin, EU-STANDS4PM Consortium, Katharina Eva Ó Cathaoir, Martin Golebiewski, Marc Kirschner*, Ingrid Kockum, Heike Moser and Dagmar Waltemath Towards standardization guidelines for in silico approaches in personalized medicine https://doi.org/10.1515/jib-2020-0006 Received February 18, 2020; accepted April 26, 2020; published online August 24, 2020 Abstract: Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stake- holder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine. -
European Bioinformatics Institute . Cambridge
EMBL-EBI Annual Report 2018 Annual European Bioinformatics Institute . Cambridge Annual Report 2018 PB EMBL-EBI Annual Report 2018 EMBL-EBI Annual Report 2018 3 © 2018 European Molecular Biology Laboratory This publication was produced by the External Relations team at EMBL’s European Bioinformatics Institute (EMBL-EBI). For more information about EMBL-EBI please contact: [email protected] 4 EMBL-EBI Annual Report 2018 EMBL-EBI Annual Report 2018 5 Table of contents Who we are 6 Foreword 9 Celebrating 25 years of EMBL-EBI 10 What we achieved in 2018 14 2018 in numbers 15 Highlights of the year 16 Progress against our strategy 18 Increasing usage, utility and application of bioinformatics 19 Extending collaboration and coordination 30 Continuous improvement, maximising efficiency 33 Building capacity and capability 36 Supporting global expansion of biomolecular resources 40 Key information 42 Financial figures 43 Organisation of EMBL-EBI leadership in 2018 44 Our governance 46 Our funders 47 List of acronyms 48 4 EMBL-EBI Annual Report 2018 EMBL-EBI Annual Report 2018 5 Who we are EMBL’s European Bioinformatics Institute (EMBL-EBI) is the world’s leading source of biological and biomolecular data. Our core mission is to enable life science research and its translation to medicine, agriculture, industry and society by providing biological data, tools and knowledge. We are part of the European Molecular Biology Laboratory (EMBL), an open science intergovernmental organisation that has grown to become Europe’s centre of excellence in life science research, services and training. EMBL is primarily funded by public research monies from over 20 member states. -
Challenges in Funding and Developing Genomic Software: Roots and Remedies Adam Siepel
Siepel Genome Biology (2019) 20:147 https://doi.org/10.1186/s13059-019-1763-7 OPINION Open Access Challenges in funding and developing genomic software: roots and remedies Adam Siepel in 2019 [6]. There were no formal mechanisms at the time Abstract for grant applications for scientific research. Instead, The computer software used for genomic analysis has William Herschel simply approached the King directly become a crucial component of the infrastructure for with a request for royal patronage. The 40-ft tele- life sciences. However, genomic software is still scope is one of the earliest examples of government typically developed in an ad hoc manner, with investment in the infrastructure for scientific research, inadequate funding, and by academic researchers not to enable a project that simply would not have been trained in software development, at substantial costs possible with private funds alone. to the research community. I examine the roots of the The model of government investment in scientific in- incongruity between the importance of and the frastructure became increasingly well-established degree of investment in genomic software, and I throughout the 19th and 20th centuries, culminating in suggest several potential remedies for current the “Big Science” of the World War II and Post-War problems. As genomics continues to grow, new eras. Science in modern times has been dominated, in strategies for funding and developing the software many ways, by these massive public investments. Prom- that powers the field will become increasingly -
Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
International Journal of Molecular Sciences Review Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis Chen Chen 1, Jie Hou 2,3, John J. Tanner 4 and Jianlin Cheng 1,* 1 Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA; [email protected] 2 Department of Computer Science, Saint Louis University, St. Louis, MO 63103, USA; [email protected] 3 Program in Bioinformatics & Computational Biology, Saint Louis University, St. Louis, MO 63103, USA 4 Departments of Biochemistry and Chemistry, University of Missouri, Columbia, MO 65211, USA; [email protected] * Correspondence: [email protected] Received: 18 March 2020; Accepted: 18 April 2020; Published: 20 April 2020 Abstract: Recent advances in mass spectrometry (MS)-based proteomics have enabled tremendous progress in the understanding of cellular mechanisms, disease progression, and the relationship between genotype and phenotype. Though many popular bioinformatics methods in proteomics are derived from other omics studies, novel analysis strategies are required to deal with the unique characteristics of proteomics data. In this review, we discuss the current developments in the bioinformatics methods used in proteomics and how they facilitate the mechanistic understanding of biological processes. We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods that have been developed to perform comprehensive analysis in proteomics studies. We conclude with a discussion of how quantitative protein data can be used to reconstruct protein interactions and signaling networks. Keywords: bioinformatics analysis; computational proteomics; machine learning 1. Introduction Proteins are essential molecules in nearly all biological processes.