Like many words, the term “immunomics” equates to different ideas contingent on context. For a brief span, immunomics meant the study of the Immunome, of which there were, in turn, several different definitions. A now largely defunct meaning rendered the Immunome as the set of antigenic peptides or immunogenic proteins within a single microorganism – be that virus, bacteria, fungus, or parasite – or microbial population, or antigenic or allergenic proteins and peptides derived from the environment as a whole, containing also proteins from eukaryotic sources. However, times have changed and the meaning of immunomics has also changed. Other newer definitions of the Immunome have come to focus on the plethora of immunological receptors and accessory molecules that comprise the host immune arsenal. Today, Immunomics or immunogenomics is now most often used as a synonym for high-throughput genome-based immunology. This is the study of aspects of the immune system using high-throughput techniques within a conc- tual landscape borne of both clinical and biophysical thinking.

Like many words, the term “immunomics” equates to different ideas contingent on context. For a brief span, immunomics meant the study of the Immunome, of which there were, in turn, several different definitions. A now largely defunct meaning rendered the Immunome as the set of antigenic peptides or immunogenic proteins within a single microorganism – be that virus, bacteria, fungus, or parasite – or microbial population, or antigenic or allergenic proteins and peptides derived from the environment as a whole, containing also proteins from eukaryotic sources. However, times have changed and the meaning of immunomics has also changed. Other newer definitions of the Immunome have come to focus on the plethora of immunological receptors and accessory molecules that comprise the host immune arsenal. Today, Immunomics or immunogenomics is now most often used as a synonym for high-throughput genome-based immunology. This is the study of aspects of the immune system using high-throughput techniques within a conc- tual landscape borne of both clinical and biophysical thinking.

In contrast to existing books on immunoinformatics, this volume presents a cross-section of immunoinformatics research. The contributions highlight the interdisciplinary nature of the field and how collaborative efforts among bioinformaticians and bench scientists result in innovative strategies for understanding the immune system. Immunoinformatics is ideal for scientists and students in immunology, bioinformatics, microbiology, and many other disciplines.

Innate immunity is one the most evolutionally conserved systems, designed to protect the organism from viruses and bacterial infections, stress and many other types of attacks from the outside world. During the past decade, the capacity of molecular biology and information technology to produce and analyse data have grown exponentially, rapidly reforming many aspects of immunology research in the post-genomics era. As a result, scientific understanding of signalling networks governing the innate immunity response in human tissues and other organisms has evolved beyond recognition, compared to even just a decade ago. Many strategies have been designed over the years to identify novel proteins, which have a crucial role in innate immunity responses by regulating particular signalling pathways. These projects had many advantages, including the definition of novel drug targets, as exemplified by the recent success of anti-TNF therapy, as well as leading to a better, system-wide understanding of the molecular control of innate immunity. In the past few years, a new concept, Immunomics, has been adopted to define an emerging, multidisciplinary field of research (Schonbach, 2003). Although rapid progress has been made to identify the proteins playing pivotal roles in the innate immunity–related signalling pathways (for example, TIR signalling pathways), the catalogue of proteins with a key regulatory function identified and studied is far from completed. Novel proteins need to be char- terised to gain a more comprehensive picture of how signalling networks are regulated.

The astounding diversity of the immune system and the complexity of its regulatory pathways makes immunology a combinatorial science. Computational analysis has therefore become an essential element of immunology research and this has led to the creation of the emerging field of immunoinformatics. This book is the first to feature thorough coverage of this new field. Immunoinformatics facilitates the understanding of immune function by modelling the interactions among immunological components. Biological research provides ever deeper insights into the complexity of living organisms while computer science provides an effective means to store and analyse large volumes of complex data. Combining the two fields increases the efficiency of biological research and offers the potential for major advances in the study of biological systems. This book encompasses key developments in immunoinformatics, including immunological databases, sequence analysis, structure modelling, mathematical modelling of the immune system, simulation of laboratory experiments, statistical support for immunological experimentation and immunogenomics. The difficulties in effective application of bioinformatic tools in immunology arise at both ends of the spectrum: most immunologists have only a limited comprehension of sophisticated data analysis and applicability and limitations, while the average computer scientist lacks knowledge of the depth and complexity of biological data. The purpose of this book, therefore, is to present contributions from a multidisciplinary team of biologists and computer scientists to explore the issues related to better understanding of immune function and, in particular, to help apply new computer science methods to immunological research. Related Novartis Foundation symposia: 247 In Silico Simulation of Biological Processes Chair: Denis Noble 252 Generation and effector functions of regulatory lymphocytes Chair: Jean-François Bach

Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

This textbook presents mathematical models in bioinformatics and describes biological problems that inspire the computer science tools used to manage the enormous data sets involved. The first part of the book covers mathematical and computational methods, with practical applications presented in the second part. The mathematical presentation avoids unnecessary formalism, while remaining clear and precise. The book closes with a thorough bibliography, reaching from classic research results to very recent findings. This volume is suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on mathematical and computer science background.