{"product_id":"bioinformatics-for-vaccinology-paperback-softback-9780470027110","title":"Bioinformatics for Vaccinology (Paperback \/ softback) 9780470027110","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eBioinformatics for Vaccinology\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eDarren R. Flower (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470027110, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePaperback \/ softback, published 7 November 2008\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e320 pages\u003cbr\u003e24.8 x 17.2 x 1.7 cm, 0.538 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e“It pulls a number of different disciplines into a concise review that illustrates the potential we have in science to change our world.” (\u003ci\u003eDoody's\u003c\/i\u003e, April 2009)  \u003cp\u003e\u003cbr\u003e \"This book may well serve as a first line of reference for all biologists and\u003cbr\u003e computer scientists. This textbook would be an excellent addition to the bookshelf of most scientists who encounter vaccinology in the drug discovery and development processes.\" ( Virology Journal - October -2009)\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003ci\u003e“… this book was written from start to finish by one extremely dedicated and erudite individual. The author has done an excellent job of covering the many topics that fall under the umbrella of computational biology for vaccine design, demonstrating an admirable command of subject matter in fields as disparate as object-oriented databases and regulation of T cell response. Simply put, it has just the right breadth and depth, and it reads well. In fact, readability is one of its virtues—making the book enticing and useful, all at once…”\u003c\/i\u003e Human Vaccines, 2010  \u003cp\u003e\u003ci\u003e\"... This book has several strong points. Although there are many textbooks that deal with vaccinology, few attempts have been made to bring together descriptions of vaccines in history, basic bioinformatics, various computational solutions and challenges in vaccinology, detailed experimental methodologies, and cutting-edge technologies... This book may well serve as a first line of reference for all biologists and computer scientists...\"\u003c\/i\u003e –Virology Journal, 2009\u003c\/p\u003e \u003cp\u003e\u003cbr\u003e Vaccines have probably saved more lives and reduced suffering in a greater number of people than any other medical intervention in human history, succeeding in eradicating smallpox and significantly reducing the mortality and incidence of other diseases. However, with the emergence of diseases such as SARS and the threat of biological warfare, vaccination has once again become a topic of major interest in public health. \u003c\/p\u003e \u003cp\u003eVaccinology now has at its disposal an array of post-genomic approaches of great power. None has a more persuasive potential impact than the application of computational informatics to vaccine discovery; the recent expansion in genome data and the parallel increase in cheap computing power have placed the bioinformatics exploration of pathogen genomes centre stage for vaccine researchers. \u003c\/p\u003e \u003cp\u003eThis is the first book to address the area of bioinformatics as applied to rational vaccine design, discussing the ways in which bioinformatics can contribute to improved vaccine development by\u003c\/p\u003e \u003cul\u003e \u003cli\u003eintroducing the subject of harnessing the mathematical and computing power inherent in bioinformatics to the study of vaccinology\u003c\/li\u003e \u003cli\u003eputting it into a historical and societal context, and \u003c\/li\u003e \u003cli\u003eexploring the scope of its methods and applications.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cb\u003e\u003ci\u003eBioinformatics for Vaccinology\u003c\/i\u003e\u003c\/b\u003e is a one-stop introduction to computational vaccinology. It will be of particular interest to bioinformaticians with an interest in immunology, as well as to immunologists, and other biologists who need to understand how advances in theoretical and computational immunobiology can transform their working practices.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003eAcknowledgements xv\u003c\/p\u003e \u003cp\u003eExordium xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Vaccines: Their place in history 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSmallpox in history 1\u003c\/p\u003e \u003cp\u003eVariolation 3\u003c\/p\u003e \u003cp\u003eVariolation in history 5\u003c\/p\u003e \u003cp\u003eVariolation comes to Britain 6\u003c\/p\u003e \u003cp\u003eLady Mary Wortley Montagu 9\u003c\/p\u003e \u003cp\u003eVariolation and the Sublime Porte 11\u003c\/p\u003e \u003cp\u003eThe royal experiment 13\u003c\/p\u003e \u003cp\u003eThe boston connection 14\u003c\/p\u003e \u003cp\u003eVariolation takes hold 17\u003c\/p\u003e \u003cp\u003eThe Suttonian method 18\u003c\/p\u003e \u003cp\u003eVariolation in Europe 19\u003c\/p\u003e \u003cp\u003eThe coming of vaccination 21\u003c\/p\u003e \u003cp\u003eEdward Jenner 23\u003c\/p\u003e \u003cp\u003eCowpox 26\u003c\/p\u003e \u003cp\u003eVaccination vindicated 28\u003c\/p\u003e \u003cp\u003eLouis Pasteur 29\u003c\/p\u003e \u003cp\u003eVaccination becomes a science 30\u003c\/p\u003e \u003cp\u003eMeister, Pasteur and rabies 31\u003c\/p\u003e \u003cp\u003eA vaccine for every disease 33\u003c\/p\u003e \u003cp\u003eIn the time of cholera 34\u003c\/p\u003e \u003cp\u003eHaffkine and cholera 36\u003c\/p\u003e \u003cp\u003eBubonic plague 37\u003c\/p\u003e \u003cp\u003eThe changing face of disease 39\u003c\/p\u003e \u003cp\u003eAlmroth wright and typhoid 40\u003c\/p\u003e \u003cp\u003eTuberculosis, Koch, and Calmette 43\u003c\/p\u003e \u003cp\u003eVaccine BCG 44\u003c\/p\u003e \u003cp\u003ePoliomyelitis 46\u003c\/p\u003e \u003cp\u003eSalk and Sabin 47\u003c\/p\u003e \u003cp\u003eDiphtheria 49\u003c\/p\u003e \u003cp\u003eWhooping cough 50\u003c\/p\u003e \u003cp\u003eMany diseases, many vaccines 51\u003c\/p\u003e \u003cp\u003eSmallpox: Endgame 53\u003c\/p\u003e \u003cp\u003eFurther reading 54\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Vaccines: Need and opportunity 55\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eEradication and reservoirs 55\u003c\/p\u003e \u003cp\u003eThe ongoing burden of disease 57\u003c\/p\u003e \u003cp\u003eLifespans 57\u003c\/p\u003e \u003cp\u003eThe evolving nature of disease 59\u003c\/p\u003e \u003cp\u003eEconomics, climate and disease 60\u003c\/p\u003e \u003cp\u003eThree threats 60\u003c\/p\u003e \u003cp\u003eTuberculosis in the 21st century 61\u003c\/p\u003e \u003cp\u003eHIV and AIDS 62\u003c\/p\u003e \u003cp\u003eMalaria: Then and now 63\u003c\/p\u003e \u003cp\u003eInfluenza 64\u003c\/p\u003e \u003cp\u003eBioterrorism 65\u003c\/p\u003e \u003cp\u003eVaccines as medicines 67\u003c\/p\u003e \u003cp\u003eVaccines and the pharmaceutical industry 68\u003c\/p\u003e \u003cp\u003eMaking vaccines 70\u003c\/p\u003e \u003cp\u003eThe coming of the vaccine industry 70\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Vaccines: How they work 73\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChallenging the immune system 73\u003c\/p\u003e \u003cp\u003eThe threat from bacteria: Robust, diverse, and endemic 74\u003c\/p\u003e \u003cp\u003eMicrobes, diversity and metagenomics 75\u003c\/p\u003e \u003cp\u003eThe intrinsic complexity of the bacterial threat 76\u003c\/p\u003e \u003cp\u003eMicrobes and humankind 77\u003c\/p\u003e \u003cp\u003eThe nature of vaccines 78\u003c\/p\u003e \u003cp\u003eTypes of vaccine 80\u003c\/p\u003e \u003cp\u003eCarbohydrate vaccines 82\u003c\/p\u003e \u003cp\u003eEpitopic vaccines 82\u003c\/p\u003e \u003cp\u003eVaccine delivery 83\u003c\/p\u003e \u003cp\u003eEmerging immunovaccinology 84\u003c\/p\u003e \u003cp\u003eThe immune system 85\u003c\/p\u003e \u003cp\u003eInnate immunity 86\u003c\/p\u003e \u003cp\u003eAdaptive immunity 88\u003c\/p\u003e \u003cp\u003eThe microbiome and mucosal immunity 90\u003c\/p\u003e \u003cp\u003eCellular components of immunity 90\u003c\/p\u003e \u003cp\u003eCellular immunity 93\u003c\/p\u003e \u003cp\u003eThe T cell repertoire 93\u003c\/p\u003e \u003cp\u003eEpitopes: The immunological quantum 94\u003c\/p\u003e \u003cp\u003eThe major histocompatibility complex 95\u003c\/p\u003e \u003cp\u003eMHC nomenclature 97\u003c\/p\u003e \u003cp\u003ePeptide binding by the MHC 98\u003c\/p\u003e \u003cp\u003eThe structure of the MHC 99\u003c\/p\u003e \u003cp\u003eAntigen presentation 101\u003c\/p\u003e \u003cp\u003eThe proteasome 101\u003c\/p\u003e \u003cp\u003eTransporter associated with antigen processing 103\u003c\/p\u003e \u003cp\u003eClass II processing 103\u003c\/p\u003e \u003cp\u003eSeek simplicity and then distrust it 104\u003c\/p\u003e \u003cp\u003eCross presentation 105\u003c\/p\u003e \u003cp\u003eT cell receptor 106\u003c\/p\u003e \u003cp\u003eT cell activation 108\u003c\/p\u003e \u003cp\u003eImmunological synapse 109\u003c\/p\u003e \u003cp\u003eSignal 1, signal 2, immunodominance 109\u003c\/p\u003e \u003cp\u003eHumoral immunity 110\u003c\/p\u003e \u003cp\u003eFurther reading 112\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Vaccines: Data and databases 113\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMaking sense of data 113\u003c\/p\u003e \u003cp\u003eKnowledge in a box 114\u003c\/p\u003e \u003cp\u003eThe science of -omes and -omics 115\u003c\/p\u003e \u003cp\u003eThe proteome 115\u003c\/p\u003e \u003cp\u003eSystems biology 116\u003c\/p\u003e \u003cp\u003eThe immunome 117\u003c\/p\u003e \u003cp\u003eDatabases and databanks 118\u003c\/p\u003e \u003cp\u003eThe relational database 119\u003c\/p\u003e \u003cp\u003eThe XML database 119\u003c\/p\u003e \u003cp\u003eThe protein universe 120\u003c\/p\u003e \u003cp\u003eMuch data, many databases 122\u003c\/p\u003e \u003cp\u003eWhat proteins do 122\u003c\/p\u003e \u003cp\u003eWhat proteins are 124\u003c\/p\u003e \u003cp\u003eThe amino acid world 124\u003c\/p\u003e \u003cp\u003eThe chiral nature of amino acids 127\u003c\/p\u003e \u003cp\u003eNaming the amino acids 130\u003c\/p\u003e \u003cp\u003eThe amino acid alphabet 132\u003c\/p\u003e \u003cp\u003eDefining amino acid properties 134\u003c\/p\u003e \u003cp\u003eSize, charge and hydrogen bonding 135\u003c\/p\u003e \u003cp\u003eHydrophobicity, lipophilicity and partitioning 136\u003c\/p\u003e \u003cp\u003eUnderstanding partitioning 139\u003c\/p\u003e \u003cp\u003eCharges, ionization, and pka 140\u003c\/p\u003e \u003cp\u003eMany kinds of property 143\u003c\/p\u003e \u003cp\u003eMapping the world of sequences 146\u003c\/p\u003e \u003cp\u003eBiological sequence databases 147\u003c\/p\u003e \u003cp\u003eNucleic acid sequence databases 148\u003c\/p\u003e \u003cp\u003eProtein sequence databases 149\u003c\/p\u003e \u003cp\u003eAnnotating databases 150\u003c\/p\u003e \u003cp\u003eText mining 151\u003c\/p\u003e \u003cp\u003eOntologies 153\u003c\/p\u003e \u003cp\u003eSecondary sequence databases 154\u003c\/p\u003e \u003cp\u003eOther databases 155\u003c\/p\u003e \u003cp\u003eDatabases in immunology 156\u003c\/p\u003e \u003cp\u003eHost databases 156\u003c\/p\u003e \u003cp\u003ePathogen databases 159\u003c\/p\u003e \u003cp\u003eFunctional immunological databases 161\u003c\/p\u003e \u003cp\u003eComposite, integrated databases 162\u003c\/p\u003e \u003cp\u003eAllergen databases 163\u003c\/p\u003e \u003cp\u003eFurther reading 165\u003c\/p\u003e \u003cp\u003eReference 165\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Vaccines: Data driven prediction of binders, epitopes and immunogenicity 167\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTowards epitope-based vaccines 167\u003c\/p\u003e \u003cp\u003eT cell epitope prediction 168\u003c\/p\u003e \u003cp\u003ePredicting MHC binding 169\u003c\/p\u003e \u003cp\u003eBinding is biology 172\u003c\/p\u003e \u003cp\u003eQuantifying binding 173\u003c\/p\u003e \u003cp\u003eEntropy, enthalpy and entropy-enthalpy compensation 174\u003c\/p\u003e \u003cp\u003eExperimental measurement of binding 175\u003c\/p\u003e \u003cp\u003eModern measurement methods 177\u003c\/p\u003e \u003cp\u003eIsothermal titration calorimetry 178\u003c\/p\u003e \u003cp\u003eLong and short of peptide binding 179\u003c\/p\u003e \u003cp\u003eThe class I peptide repertoire 180\u003c\/p\u003e \u003cp\u003ePracticalities of binding prediction 181\u003c\/p\u003e \u003cp\u003eBinding becomes recognition 182\u003c\/p\u003e \u003cp\u003eImmunoinformatics lends a hand 183\u003c\/p\u003e \u003cp\u003eMotif based prediction 184\u003c\/p\u003e \u003cp\u003eThe imperfect motif 185\u003c\/p\u003e \u003cp\u003eOther approaches to binding prediction 186\u003c\/p\u003e \u003cp\u003eRepresenting sequences 187\u003c\/p\u003e \u003cp\u003eComputer science lends a hand 188\u003c\/p\u003e \u003cp\u003eArtificial neural networks 188\u003c\/p\u003e \u003cp\u003eHidden Markov models 190\u003c\/p\u003e \u003cp\u003eSupport vector machines 190\u003c\/p\u003e \u003cp\u003eRobust multivariate statistics 191\u003c\/p\u003e \u003cp\u003ePartial least squares 191\u003c\/p\u003e \u003cp\u003eQuantitative structure activity relationships 192\u003c\/p\u003e \u003cp\u003eOther techniques and sequence representations 193\u003c\/p\u003e \u003cp\u003eAmino acid properties 194\u003c\/p\u003e \u003cp\u003eDirect epitope prediction 195\u003c\/p\u003e \u003cp\u003ePredicting antigen presentation 196\u003c\/p\u003e \u003cp\u003ePredicting class II MHC binding 197\u003c\/p\u003e \u003cp\u003eAssessing prediction accuracy 199\u003c\/p\u003e \u003cp\u003eROC plots 202\u003c\/p\u003e \u003cp\u003eQuantitative accuracy 203\u003c\/p\u003e \u003cp\u003ePrediction assessment protocols 204\u003c\/p\u003e \u003cp\u003eComparing predictions 206\u003c\/p\u003e \u003cp\u003ePrediction versus experiment 207\u003c\/p\u003e \u003cp\u003ePredicting B cell epitopes 208\u003c\/p\u003e \u003cp\u003ePeak profiles and smoothing 209\u003c\/p\u003e \u003cp\u003eEarly methods 210\u003c\/p\u003e \u003cp\u003eImperfect B cell prediction 211\u003c\/p\u003e \u003cp\u003eReferences 212\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Vaccines: Structural approaches 217\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eStructure and function 217\u003c\/p\u003e \u003cp\u003eTypes of protein structure 219\u003c\/p\u003e \u003cp\u003eProtein folding 220\u003c\/p\u003e \u003cp\u003eRamachandran plots 221\u003c\/p\u003e \u003cp\u003eLocal structures 222\u003c\/p\u003e \u003cp\u003eProtein families, protein folds 223\u003c\/p\u003e \u003cp\u003eComparing structures 223\u003c\/p\u003e \u003cp\u003eExperimental structure determination 224\u003c\/p\u003e \u003cp\u003eStructural genomics 226\u003c\/p\u003e \u003cp\u003eProtein structure databases 227\u003c\/p\u003e \u003cp\u003eOther databases 228\u003c\/p\u003e \u003cp\u003eImmunological structural databases 229\u003c\/p\u003e \u003cp\u003eSmall molecule databases 230\u003c\/p\u003e \u003cp\u003eProtein homology modelling 231\u003c\/p\u003e \u003cp\u003eUsing homology modelling 232\u003c\/p\u003e \u003cp\u003ePredicting MHC supertypes 233\u003c\/p\u003e \u003cp\u003eApplication to alloreactivity 235\u003c\/p\u003e \u003cp\u003e3D-QSAR 236\u003c\/p\u003e \u003cp\u003eProtein docking 238\u003c\/p\u003e \u003cp\u003ePredicting B cell epitopes with docking 238\u003c\/p\u003e \u003cp\u003eVirtual screening 240\u003c\/p\u003e \u003cp\u003eLimitations to virtual screening 241\u003c\/p\u003e \u003cp\u003ePredicting epitopes with virtual screening 243\u003c\/p\u003e \u003cp\u003eVirtual screening and adjuvant discovery 244\u003c\/p\u003e \u003cp\u003eAdjuvants and innate immunity 245\u003c\/p\u003e \u003cp\u003eSmall molecule adjuvants 246\u003c\/p\u003e \u003cp\u003eMolecular dynamics and immunology 248\u003c\/p\u003e \u003cp\u003eMolecular dynamics methodology 249\u003c\/p\u003e \u003cp\u003eMolecular dynamics and binding 249\u003c\/p\u003e \u003cp\u003eImmunological applications 250\u003c\/p\u003e \u003cp\u003eLimitations of molecular dynamics 251\u003c\/p\u003e \u003cp\u003eMolecular dynamics and high performance computing 252\u003c\/p\u003e \u003cp\u003eReferences 253\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Vaccines: Computational solutions 257\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eVaccines and the world 257\u003c\/p\u003e \u003cp\u003eBioinformatics and the challenge for vaccinology 259\u003c\/p\u003e \u003cp\u003ePredicting immunogenicity 260\u003c\/p\u003e \u003cp\u003eComputational vaccinology 261\u003c\/p\u003e \u003cp\u003eThe threat remains 262\u003c\/p\u003e \u003cp\u003eBeyond empirical vaccinology 262\u003c\/p\u003e \u003cp\u003eDesigning new vaccines 263\u003c\/p\u003e \u003cp\u003eThe perfect vaccine 264\u003c\/p\u003e \u003cp\u003eConventional approaches 265\u003c\/p\u003e \u003cp\u003eGenome sequences 266\u003c\/p\u003e \u003cp\u003eSize of a genome 267\u003c\/p\u003e \u003cp\u003eReverse vaccinology 268\u003c\/p\u003e \u003cp\u003eFinding antigens 269\u003c\/p\u003e \u003cp\u003eThe success of reverse vaccinology 271\u003c\/p\u003e \u003cp\u003eTumour vaccines 273\u003c\/p\u003e \u003cp\u003ePrediction and personalised medicine 275\u003c\/p\u003e \u003cp\u003eImperfect data 276\u003c\/p\u003e \u003cp\u003eForecasting and the future of computational vaccinology 277\u003c\/p\u003e \u003cp\u003eIndex 283\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Biology, life sciences [\u003ca title=\"See our other books on Biology, life sciences\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Biology,%20life%20sciences%20%5BPS%5D%22\"\u003ePS\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand 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