Buch, Englisch, 526 Seiten, Format (B × H): 178 mm x 254 mm
Reihe: Methods in Molecular Biology
Buch, Englisch, 526 Seiten, Format (B × H): 178 mm x 254 mm
Reihe: Methods in Molecular Biology
ISBN: 978-1-0716-5841-3
Verlag: Springer Us
This volume presents a collection of the latest computational methods and protocols used in molecular microbiology, with a focus on their application to gain systems-level understanding of molecular processes within microorganisms. The chapters in this book cover topics such as metabolic pathway analysis for prokaryotes; phenotype-based prediction of host–virus interactions; computational prediction of host-microbe protein-protein Interactions; plasmid annotation and pangenome analysis; and Bayesian reconstruction of SARS-CoV-2 transmission networks. Written in the highly successful series format, chapters include introductions to their respective topics, lists of the necessary materials and tools, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Practical and comprehensive, is a useful resource for educators and researchers working in the field of microbiology. It will help to familiarize them with state-of-the-art computational protocols for molecular microbiological data analysis and teach them about their usage through step-by-step instructions by their developers or expert users.
Chapter 2 is available open access under a Creative Commons Attribution 3.0 IGO License via link.springer.com.
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Weitere Infos & Material
Metabolic Pathway Analysis for Prokaryotes.- Viral Non-Coding RNA Structure Annotation and API-Based Data Retrieval with Rfam and R2DT.- A Computational Framework for Identifying Genomic Islands using Jensen-Shannon Divergence and Codon Bias (JS-CB).- Phenotype Based Prediction of Host–Virus Interactions.- Computational Prediction of DNA Phage–Host Interaction: Complete Workflow, Quality Control, and Interpretation.- Identifying Plant-Pathogen NLR-Effector Interactions with Deep Learning Approaches.- A Standardized Protocol for Artificial Intelligence and Machine Learning (AI-ML) Tools for Bioprocess Optimization.- Optimization of Parameter Selection for Analysis of 16S Amplicon Sequencing Data Generated by High-Throughput Sequencing.- Effective Batch-to-Batch Error Correction in Untargeted Metabolomics with Isotopic Ratio Outlier Analysis (IROA) Using Suppression Correction and Dual MSTUS Normalization.- Computational Prediction of Host-Microbe Protein-Protein Interactions: From Data to Discovery.- Oxford Nanopore Technologies-Based Single Guide RNA Amplicon Sequencing and Extraction of Spacer Sequences for CRISPRi-Based Functional Genomics.- Bacterial Genome Assembly from Oxford Nanopore Technologies Long Reads and Genomic Characterization.- A Workflow for Microscopy-Based Bacterial Cell Segmentation and Quantification.- Galaxy-Based Workflow for Differential Gene Expression Analysis using RNA-seq Data.- Prediction of Source Nutrients for Microorganisms Using Metabolic Networks.- Plasmid Annotation and Pangenome Analysis.- Integrated Workflow for Label-Free Proteomics and Pathway Analysis in Yeast Using LC-MS/MS.- A Microbiome Analysis Pipeline.- A Protocol for Dual-Reference Taxonomic and Diversity Profiling of Microbial 16S rRNA Amplicon Data Using QIIME 2.- Pathogen Detection Using Machine Learning.- Bayesian Reconstruction of SARS-CoV-2 Transmission Networks Using Outbreaker2.
