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Preface. <p>List of contributors.</p> <p><b>1. Genotyping methods and disease gene identification</b> (<i>Ramón Kucharzak and Ivo Glynne Gut</i>).</p> <p>1.1  Introduction.</p> <p>1.2  Genotyping of single-nucleotide polymorphisms.</p> <p>1.3  Methods for interrogating SNPs.</p> <p>1.4  Analysis formats.</p> <p>1.5  The current generation of methods for SNP genotyping.</p> <p>1.6  The next generation.</p> <p>1.7  Classical HLA typing.</p> <p>1.8   MHC haplotypes.</p> <p>1.9   Molecular haplotyping.</p> <p>1.10  Microhaplotyping.</p> <p>1.11  MHC and disease association.</p> <p>1.12   Conclusions.</p> <p><b>2. Glycomics and the Sugar Code: Primer to their Structural Basis and Functionality</b> (<i>Hans-Joachim Gabius</i>).</p> <p>2.1  Introduction.</p> <p>2.2  Lectins as effectors in functional glycomics.</p> <p>2.3  Galectins: structural principles and intrafamily diversity.</p> <p>2.4  Ligand-dependent levels of affinity regulation.</p> <p>2.5  Perspectives for galectin-dependent medical applications.</p> <p>2.6  Conclusions.</p> <p><b>3. Proteomics in Clinical Research: Perspectives and Expectations</b> (<i>Ivan Lefkovits, Thomas Grussenmeyer, Peter Matt, Martin Grapow, Michael Lefkovits and Hans-Reinhard Zerkowski</i>).</p> <p>3.1   Introduction.</p> <p>3.2   Proteomics: tools and projects.</p> <p>3.3   Discussion.</p> <p>3.4   Concluding remarks.</p> <p><b>4. Chemical genomics: bridging the gap between novel targets and small molecule drug candidates. Contribution to immunology</b> (<i>György Dormán, Takenori Tomohiro, Yasumaru Hatanaka and Ferenc Darvas</i>).</p> <p>4.1   Introduction of chemical genomics: definitions.</p> <p>4.2   Chemical microarrays.</p> <p>4.3   Small molecule and peptide probes for studying binding interactions through creating a covalent bond.</p> <p>4.4   Photochemical proteomics.</p> <p>4.5   General aspects of photoaffinity labelling.</p> <p>4.6   Summary.</p> <p><b>5. Genomic and proteomic analysis of activated human monocytes</b> (<i>Ameesha Batheja, George Ho, Xiaoyao Xiao, Xiwei Wang and David Uhlinger</i>).</p> <p>5.1    Primary human monocytes, as a model system.</p> <p>5.2    Transcriptional profiling of activated monocytes.</p> <p>5.3    Functional genomics.</p> <p>5.4    Proteomic analysis of activated human monocytes.</p> <p><b>6. Bioinformatics as a problem of knowlege representation: applications to some aspects of immunoregulation</b> (<i>Sándor Pongor and András Falus</i>).</p> <p>6.1    Introduction.</p> <p>6.2    Sequences and languages.</p> <p>6.3    Three-dimensional models.</p> <p>6.4    Genomes, proteomes, networks.</p> <p>6.5    Computational tools.</p> <p>6.6    Information processing in the immune system.</p> <p>6.7    Concluding remarks</p> <p> <b>7. Immune responsiveness of human tumours</b> (<i>Ena Wang and Francesco M. Marincola</i>).</p> <p>7.1   Introduction.</p> <p>7.2   Defining tumour immune responsiveness.</p> <p>7.3   Studying immune responsiveness in human tumours.</p> <p>7.4   Immune responsiveness in the context of therapy.</p> <p>7.5   The spatial dimension in the quest for the target.</p> <p>7.6   Studying the receiving end – tumour as an elusive target for immune recognition.</p> <p>7.7    The role of the host in determining immune responsiveness.</p> <p>7.8    Concluding remarks.</p> <p><b>8. Chemokines regulate leukocyte trafficking and organ-specific metastasis</b> (<i>Andor Pivarcsi, Anja Mueller and Bernhard Homey</i>).</p> <p>8.1   Chemokines and chemokine receptors.</p> <p>8.2   Chemokine receptors in the organ-specific recruitment of tumour cells.</p> <p>8.3   Cancer therapy using chemokine receptor inhibitors.</p> <p>8.4   Conclusions.</p> <p> <b>9. Towards a unified approach to new target discovery in breast cancer: combining the power of genomics, proteomics and immunology</b> (<i>Laszlo</i> <i>G. Radvanyi, Bryan Hennessy, Kurt Gish, Gordon Mills and Neil Berinstein</i>).</p> <p>9.1  Introduction.</p> <p>9.2  The use of CGH and DNA microarray-based transcriptional profiling for new target discovery in breast cancer.</p> <p>9.3  The challenge of new tumour marker/target validation: traditional techniques meet new proteomics tools.</p> <p>9.4  Immunological validation of new target genes in breast cancer: the emerging concept of the cancer ‘immunome’.</p> <p>9.5  Future prospects: combining target discovery approaches in unified publicly accessible databases.</p> <p><b>10. Genomics and Functional Differences of Dendritic Cell Subsets</b> (<i>Peter Gogolak and Eva Rajnavölgyi</i>).</p> <p>10.1   Introduction.</p> <p>10.2   Origin, differentiation and function of human dendritic cell subsets.</p> <p>10.3   Tissue localization of dendritic cell subsets.</p> <p>10.4   Antigen uptake by dentritic cells.</p> <p>10.5   Antigen processing and presentation by dendritic cells.</p> <p>10.6    Activation and polarization of dendritic cells.</p> <p>10.7    Enhancement of inflammatory responses by NK cells.</p> <p>10.8    Suppression of inflammatory responses by natural regulatory T cells.</p> <p>10.9    The role of dendritic cells and T-lymphocytes in tumour-specific immune responses.</p> <p><b>11. Systemic lupus erythematosus: new ideas for diagnosis and treatment</b> (<i>Sandeep Krishnan and George C. Tsokos</i>).</p> <p>11.1  Introduction.</p> <p>11.2  Strategies for identifying diagnostic markers.</p> <p>11.3  Strategies for gene therapy for SLE.</p> <p>11.4  Conclusion and future direction.</p> <p><b>12. Immunogenetics of experimentally induced arthritis</b> (<i>Tibor T. Glant and Vyacheslav A. Adarichev</i>).</p> <p>12.1  Rheumatoid arthritis in humans and murine proteoglycan-induced arthritis: introduction.</p> <p>12.2  Genetic linkage analysis of PGIA.</p> <p>12.3  Transcriptome picture of the disease: gene expression during initiation and progression of joint inflammation.</p> <p>12.4  Conclusions.</p> <p><b>13. Synovial activation in rheumatoid arthiritis</b> (<i>Lars C. Huber, Renate E. Gay and Steffen Gay</i>).</p> <p>13.1  Introduction.</p> <p>13.2  Synovial activation in rheumatoid arthritis.</p> <p>13.3  Conclusions/perspectives.</p> <p><b>14. T cell epitope hierarchy in experimental autoimmune models</b> (<i>Edit Buzas</i>).</p> <p>14.1  Introduction.</p> <p>14.2  Immunodominance and crypticity.</p> <p>14.3  Epitope spreading (endogenous self-priming).</p> <p>14.4  Degenerate T cell epitope recognition.</p> <p>14.5  The self-reactive TCR repertoire.</p> <p>14.6  Thymic antigen presentation.</p> <p>14.7  Peripheral antigen presentation.</p> <p>14.8  Epitope hierarchy in experimental autoimmune encephalomyelitis.</p> <p>14.9  Epitope hierarchy in aggrecan-induced murine arthritis.</p> <p>14.10  Summary.</p> <p><b>15. Gene–gene interactions in immunology as exemplified by studies on autoantibodies against 60 kDa heat-shock protein</b>  (<i>Zoltán Prohászka</i>).</p> <p>15.1  Introduction.</p> <p>15.2  Basic features of gene–gene interactions.</p> <p>15.3  How to detect epistasis.</p> <p>15.4  Autoimmunity to heat-shock proteins.</p> <p>15.5  Epistatic effect in the regulation of anti-HSP6 autoantibody levels.</p> <p>15.6  Conclusions.</p> <p><b>16. Histamine genomics and metabolomics</b> (<i>Andras Falus, Hargita Hegyesi, Susan Darvas, Zoltan Pos and Peter Igaz</i>).</p> <p>16.1  Introduction.</p> <p>16.2  Chemistry.</p> <p>16.3  Biosynthesis and biotransformation.</p> <p>16.4  Histidine decarboxylase gene and protein.</p> <p>16.5  Catabolic pathways of histamine.</p> <p>16.6  Histamine receptors.</p> <p>16.7  Histamine and cytokines, relation to the T cell polarization of the immune response.</p> <p>16.8  Histamine and tumour growth.</p> <p>16.9  Histamine research: an insight into metabolomics, lessons from HDC-deficient mice.</p> <p>16.10  Histamine genomics on databases.</p> <p><b>17. The histamine H₄ receptor: drug discovery in the post-genomic era</b>(<i>Niall O’Donnell, Paul J. Dunford and Robin L. Thurmond</i>).</p> <p>17.1  Introduction.</p> <p>17.2  Cloning of H₃R and H₄R.</p> <p>17.3  Generation of H₄R-specific antagonists.</p> <p>17.4  High-throughput screening.</p> <p>17.5  Functional studies.</p> <p>17.6  Future prospects.</p> <p><b>18. Application of microarray technology to bronchial asthma</b> (<i>Kenji Izuhara, Kazuhiko Arima, Sachiko Kanaji, Kiyonari Masumoto and Taisuke Kanaji</i>).</p> <p>18.1  Introduction.</p> <p>18.2  Lung tissue as ‘source’.</p> <p>18.3  Particular cell as ‘source’.</p> <p>18.4  Conclusions.</p> <p><b>19. Genomic investigation of asthma in human and animal models</b> (<i>Csaba Szalai</i>).</p> <p>19.1  Introduction.</p> <p>19.2  Methods for localization of asthma susceptibility genes.</p> <p>19.3  Results of the association studies and genome-wide screens in humans.</p> <p>19.4  Animal models of asthma.</p> <p>19.5  Concluding remarks.</p> <p><b>20. Primary immunodeficiencies: genotype–phenotype correlations</b> (<i>Mauno Vihinen and Anne Durandy</i>).</p> <p>20.1  Introduction.</p> <p>20.2  Immunodeficiency data services.</p> <p>20.3  Genotype–phenotype correlations.</p> <p>20.4  ADA deficiency.</p> <p>20.5  RAG1 and RAG2 deficiency.</p> <p>20.6  AID deficiency.</p> <p>20.7  WAS.</p> <p>20.8  XLA.</p> <p>20.9  Why GP correlations are not more common.</p> <p><b>21. Transcriptional profiling of dentritic cells in response to pathogens</b> (<i>Maria Foti, Francesca Granucci, Mattia Pelizzola, Norman Pavelka, Ottavio Beretta, Caterina Vizzardelli, Matteo Urbano, Ivan Zanoni, Giusy Capuano, Francesca Mingozzi and Paola Ricciardi-Castagnoli</i>).</p> <p>21.1  Transcriptional profiling to study the complexity of the immune system.</p> <p>21.2  DC subsets and functional studies.</p> <p>21.3  DC at the intersection between innate and adaptive immunity.</p> <p>21.4  DC and infectious diseases.</p> <p>21.5  DC and bacteria interaction.</p> <p>21.6  DC and virus interaction.</p> <p>21.7  DC and parasite interaction.</p> <p>21.8  <i>Leishmania mexicana</i> molecular signature.</p> <p>21.9  Conclusions.</p> <p><b>22. Parallel biology: a systematic approach to drug target and biomarker discovery in chronic obstructive pulmonary disease</b> (<i>Laszlo Takacs</i>).</p> <p>22.1  Introduction.</p> <p>22.2  Genome research is a specific application of parallel biology often regarded as systems biology.</p> <p>22.3  Chronic obstructive pulmonary disease.</p> <p>22.4  Goals of the study.</p> <p>22.5  Methods.</p> <p>22.6  Results.</p> <p><b>23. Mycobacterial granulomas: a genomic approach</b> (<i>Laura H. Hogan, Dominic O. Co and Matyas Sandor</i>).</p> <p>23.1  Introduction.</p> <p>23.2  Initial infection of macrophage.</p> <p>23.3  Mycobacterial gene expression in the host.</p> <p>23.4  Host genes important to granuloma formation.</p> <p>23.5  Granulomatous inflammation as an ecological system.</p> <p><b>Index.</b></p>

"…the first book attempting to review the current bioinformatics literature as it specifically applies to the immune system…should prove valuable to researchers interested in immunogenetics." (<i>Doody's Health Services</i>)

<b>Andras Falus</b> is Chairman of the Department of Genetics, Cell and Immunobiology at Semmelweis Medical University in Budapest and a Member of the Hungarian Academy of Sciences. He has written and edited several books on immunology, particularly histamine.

One of the major features that distinguishes vertebrates from invertebrates is the presence of a complex immune system. Over millions of years, many novel immune genes and gene families have emerged and their products form sophisticated pathways conferring protection against most pathogens. The Human Genome Project revealed that the immunoglobulin gene superfamily was one of the largest in the genome, containing more than 2% of all known human genes. High-throughput technologies for the study of DNA, mRNA and proteins, such as  microarrays and real-time gene amplification technologies, as well as biobank facilities, are enabling the investigation of these genes and pathways in ever more detail. The parallel development of databases and bioinformatics tools to store and interpret this information will also contribute to greater understanding of the function of the immune system. <p>Genomics is finally changing from an academic discipline to one with real clinical relevance. The study of immune regulation in response to pathogen invasion, to the presence of malignant or allogeneic tissue and, in some cases, to normal autologous tissue requires techniques that study the behaviour of whole systems in parallel. A genome-wide, systems biology approach is needed to understand the genetic and environmental factors that regulate the healthy immune system and its response to pathogens as well as to malignant cells arising within the body. It will also facilitate determining what goes wrong when the immune system attacks normal host cells, as in autoimmune diseases such as Type 1 diabetes.</p> <p>Finally, greater knowledge of the immune system will enable us to use it to promote health and cure disease, through vaccine development – targeting both pathogens and tumour cells – and by manipulation of cellular and humoral defences.</p> <p>This book provides an overview of key conceptual and molecular technologies being deployed in immunogenomics, followed by detailed evaluations of the impact of genomics and systems biology on important areas such as cancer immunology, autoimmunity, allergy and the response to infection. It will be of interest to all those working in immunology, as well as to bioinformaticians and specialists such as oncologists and microbiologists.</p>

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