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<p>(In English) This book provides a complete overview of computational immunology, from basic concepts to mathematical modeling at the single molecule, cellular, organism, and population levels. It showcases modern mechanistic models and their use in making predictions, designing experiments, and elucidating underlying biochemical processes. It begins with an introduction to data analysis, approximations, and assumptions used in model building. Core chapters address models and methods for studying immune responses, with fundamental concepts clearly defined. Readers from immunology, quantitative biology, and applied physics will benefit from the following: Fundamental principles of computational immunology and modern quantitative methods for studying immune response at the single molecule, cellular, organism, and population levels. An overview of basic concepts in modeling and data analysis. Coverage of topics where mechanistic modeling has contributed substantially to current understanding. Discussion of genetic diversity of the immune system, cell signaling in the immune system, immune response at the cell population scale, and ecology of host-pathogen interactions.</p>
<p>(In English) This book provides a complete overview of computational immunology, from basic concepts to mathematical modeling at the single molecule, cellular, organism, and population levels. It showcases modern mechanistic models and their use in making predictions, designing experiments, and elucidating underlying biochemical processes. It begins with an introduction to data analysis, approximations, and assumptions used in model building. Core chapters address models and methods for studying immune responses, with fundamental concepts clearly defined. Readers from immunology, quantitative biology, and applied physics will benefit from the following: Fundamental principles of computational immunology and modern quantitative methods for studying immune response at the single molecule, cellular, organism, and population levels. An overview of basic concepts in modeling and data analysis. Coverage of topics where mechanistic modeling has contributed substantially to current understanding. Discussion of genetic diversity of the immune system, cell signaling in the immune system, immune response at the cell population scale, and ecology of host-pathogen interactions.</p>
<p class="recco">Recommended by Agriculture and Agri-Food Canada, a GC Data Community partner</p>
<p class="recco">Recommended by Agriculture and Agri-Food Canada, a GC Data Community partner</p>
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[[Image:Les-donnees-administratives-publiques-dans-l-espace-numerique.jpg|150px|Les données administratives publiques dans l'espace numérique]]
<h3 style="text-decoration:none;">[https://www.worldcat.org/title/donnes-administratives-publiques-dans-lespace-numrique/oclc/1281673459/editions?referer=di&editionsView=true Public administrative data in the digital space]</h3>
<p class="author">[https://wiki.gccollab.ca/Data_Conference_2022_Speakers#Pierre_Desrochers Pierre Desrochers]</p>
<p>(In French - original title: <strong>Les données administratives publiques dans l'espace numérique</strong>) The purpose of this book is to explore the issues related to the collection and use of administrative data. These data, accumulated by government departments and agencies in the course of their daily activities, are becoming more and more interesting as statistical and technological tools develop and allow their exploitation. Administrative data is data that is routinely collected when individuals register or conduct transactions, or created during record-keeping activities related to service delivery. The implications of megadata, or Big Data, the advent of machine learning and artificial intelligence are significant for organizations and their information governance. They raise many issues of quality, accuracy, privacy and interpretation.</p>
<p class="recco">Recommended by the GC Data Community</p>
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