Vijaykumar Yogesh Muley – författare

This volume explores computational methods for the rapid analysis of viral infections and strategies for their mitigation, which have significantly advanced the understanding of viral pathogenesis and host responses. Beginning with methods for identifying viral genomes from metagenomic sequencing data, the book progresses to topics such as next-generation sequencing to study host responses against viral infections, virus-host protein interactions to identify therapeutic targets, viral taxonomy, zoonotic transmission, reverse zoonosis, and antivirals, including their mechanisms of action, focusing on virus entry and life cycle. Practical workflows for identifying potential drug-like compounds from resources such as PubChem are also covered. Written for the highly successful Methods in Molecular Biology series, chapters include detailed implementation advice to ensure successful experimental results.  Authoritative and practical, Computational Virology provides researchers, students, and professionals in virology, bioinformatics, artificial intelligence, and systems biology with critical insights into the challenges posed by viral pathogens.

This volume explores computational methods for the rapid analysis of viral infections and strategies for their mitigation, which have significantly advanced the understanding of viral pathogenesis and host responses. Beginning with methods for identifying viral genomes from metagenomic sequencing data, the book progresses to topics such as next-generation sequencing to study host responses against viral infections, virus-host protein interactions to identify therapeutic targets, viral taxonomy, zoonotic transmission, reverse zoonosis, and antivirals, including their mechanisms of action, focusing on virus entry and life cycle. Practical workflows for identifying potential drug-like compounds from resources such as PubChem are also covered. Written for the highly successful Methods in Molecular Biology series, chapters include detailed implementation advice to ensure successful experimental results.  Authoritative and practical, Computational Virology provides researchers, students, and professionals in virology, bioinformatics, artificial intelligence, and systems biology with critical insights into the challenges posed by viral pathogens.

​​ ​Using genome sequencing, one can predict possible interactions among proteins. There are very few titles that focus on protein-protein interaction predictions in bacteria. The authors will describe these methods and further highlight its use to predict various biological pathways and complexity of the cellular response to various environmental conditions. Topics include analysis of complex genome-scale protein-protein interaction networks, effects of reference genome selection on prediction accuracy, and genome sequence templates to predict protein function.