Darren D.R. Flower – författare

Whatever its final readership and impact, we, the Editors, feel this book is im­ portant. It addresses the realisation that there is a deep and abiding synergy, albeit one only now being properly explored and exploited, between immunol­ ogy and computational science. This area of intersection we christen in silico immunology. Immunology is an inspiration for computational scientists seek­ ing practical and philosophical metaphors for their work; but, at the same time, it is itself a biological discipline of such discombobulating complexity that only computational help as different as simulation and data warehousing can make its modern study tractable. Thus immunology both inspires but also requires computational science. This book deals in detail with the three main areas of in silico immunology: theoretical immunology, immunoinformatics, and artificial immune systems. While all of these are now well-established the interactions between the three are only beginning to be developed. It is a truly exciting time to be working in in silicio immunology. We are reaching a critical mass that will enable great strides to be taken and significant achievements to be made. Like David Hume, we may yet come to regret that this book falls still born from the press but we hope not. Hopefully it will instead strike a cord and tap into a burgeoning Zeitgeist ready to capitalise on the remarkable potential that is in silico immunology.

Whatever its final readership and impact, we, the Editors, feel this book is im­ portant. It addresses the realisation that there is a deep and abiding synergy, albeit one only now being properly explored and exploited, between immunol­ ogy and computational science. This area of intersection we christen in silico immunology. Immunology is an inspiration for computational scientists seek­ ing practical and philosophical metaphors for their work; but, at the same time, it is itself a biological discipline of such discombobulating complexity that only computational help as different as simulation and data warehousing can make its modern study tractable. Thus immunology both inspires but also requires computational science. This book deals in detail with the three main areas of in silico immunology: theoretical immunology, immunoinformatics, and artificial immune systems. While all of these are now well-established the interactions between the three are only beginning to be developed. It is a truly exciting time to be working in in silicio immunology. We are reaching a critical mass that will enable great strides to be taken and significant achievements to be made. Like David Hume, we may yet come to regret that this book falls still born from the press but we hope not. Hopefully it will instead strike a cord and tap into a burgeoning Zeitgeist ready to capitalise on the remarkable potential that is in silico immunology.

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.

Whatever its final readership and impact, we, the Editors, feel this book is im­ portant. It addresses the realisation that there is a deep and abiding synergy, albeit one only now being properly explored and exploited, between immunol­ ogy and computational science. This area of intersection we christen in silico immunology. Immunology is an inspiration for computational scientists seek­ ing practical and philosophical metaphors for their work; but, at the same time, it is itself a biological discipline of such discombobulating complexity that only computational help as different as simulation and data warehousing can make its modern study tractable. Thus immunology both inspires but also requires computational science. This book deals in detail with the three main areas of in silico immunology: theoretical immunology, immunoinformatics, and artificial immune systems. While all of these are now well-established the interactions between the three are only beginning to be developed. It is a truly exciting time to be working in in silicio immunology. We are reaching a critical mass that will enable great strides to be taken and significant achievements to be made. Like David Hume, we may yet come to regret that this book falls still born from the press but we hope not. Hopefully it will instead strike a cord and tap into a burgeoning Zeitgeist ready to capitalise on the remarkable potential that is in silico immunology.