Muley | Computational Virology | Buch | 978-1-0716-4545-1 | sack.de

Buch, Englisch, 324 Seiten, Book w. online files / update, Format (B × H): 183 mm x 260 mm, Gewicht: 829 g

Reihe: Methods in Molecular Biology

Muley

Computational Virology


Erscheinungsjahr 2025
ISBN: 978-1-0716-4545-1
Verlag: Springer US

Buch, Englisch, 324 Seiten, Book w. online files / update, Format (B × H): 183 mm x 260 mm, Gewicht: 829 g

Reihe: Methods in Molecular Biology

ISBN: 978-1-0716-4545-1
Verlag: Springer US


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 series, chapters include detailed implementation advice to ensure successful experimental results.

Authoritative and practical, provides researchers, students, and professionals in virology, bioinformatics, artificial intelligence, and systems biology with critical insights into the challenges posed by viral pathogens.

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Weitere Infos & Material


Bioinformatic Identification of Viral Genomes from High-Throughput Metagenomic Sequencing Data.- Studying Host Transcription Responses to Viral Infections: Transcriptome Assembly and Gene Expression Quantification Using Rsubread, HISAT2, and STAR with Public RNA-Seq Data.- Deciphering Host Differential Gene Expression in Viral Infections through Public RNA-Seq Data from NCBI-GEO.- Functional Insights through Gene Ontology, Disease Ontology, and KEGG Pathway Enrichment.- Bipartite Graph Analysis of the Virus-Host Protein Interaction Network to Identify Key Proteins Mediating Infection.- Computational Approach for Detection and Analysis of Human-Virus Protein-Protein Interactions.- Exploring Virus Taxonomy, Nomenclature, and Classification.- BV-BRC Zoonosis or Reverse Zoonosis Example.- Exploring Virus Protein Domains: Detection and Evolutionary Insights.- Scalable Epidemic Simulation Using FAVITES-Lite.- Generative Artificial Intelligence for Virology.- Deciphering Genomic Complexity: The Role of Explainable AI in Evolutionary Genomics.- Next Generation Sequencing in Viral Diagnosis.- Diverse Facets of Non-Human Sequences in Read Outputs of the Human Next-Generation Sequencing Data and Their Relevance with Viruses.- Targeting Key Stages of the Viral Entry and Life Cycle: A Comprehensive Overview of the Mechanisms of Antiviral Actions.- A Python-Based Workflow for Computing and Extracting Drug-Like Compounds from PubChem.- Identifying Communities in the Virus-Host Protein-Protein Interaction Networks.



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