ISBN-13: 9789811982248 / Angielski / Twarda / 2023 / 234 str.
ISBN-13: 9789811982248 / Angielski / Twarda / 2023 / 234 str.
This book illustrates the importance and significance of the systems approach in deciphering diverse aspects of host-parasite interactions in infection dynamics. It describes the complex issues and state-of-the-art progress in the infection biology of parasitic protozoa. The book explores the current concepts and paradigms of gene expression, metabolome, and immune remodeling in these diseases. The chapters encompass updates on the parasitic tropism, co-evolution, systemic responses in hosts, and translational approaches. It provides an overview of the parasite's efficient ways of exploiting host molecules and describes pathways for their survival, differentiation, and replication within the host cells. The book also delineates the role of inflammasomes and their activation in response to the protozoan parasite. The book discusses technological progress and machine learning-based modeling approaches to revisit parasitic infection from a non-conventional perspective. Collectively this book offers a comprehensive purview of concepts and paradigms in parasitic infection in the form of an updated yet discernible elucidation.
This book illustrates the importance and significance of the systems approach in deciphering diverse aspects of host-parasite interactions in infection dynamics. It describes the complex issues and state-of-the-art progress in the infection biology of parasitic protozoa. The book explores the current concepts and paradigms of gene expression, metabolome, and immune remodeling in these diseases. The chapters encompass updates on the parasitic tropism, co-evolution, systemic responses in hosts, and translational approaches. It provides an overview of the parasite's efficient ways of exploiting host molecules and describes pathways for their survival, differentiation, and replication within the host cells. The book also delineates the role of inflammasomes and their activation in response to the protozoan parasite. The book discusses technological progress and machine learning-based modeling approaches to revisit parasitic infection from a non-conventional perspective. Collectively this book offers a comprehensive purview of concepts and paradigms in parasitic infection in the form of an updated yet discernible elucidation.