What is it about?
Microbial communities play essential roles in human health and the environment, but identifying and understanding them requires advanced computational approaches. This chapter explains how metagenomic sequencing data can be used to classify microorganisms and uncover their evolutionary relationships using the Galaxy platform. It introduces practical workflows for quality control, taxonomic and phylogenetic classification, and visualization with tools such as MetaPhlAn2, Krona, and GraPhlAn, demonstrating how these methods help reveal microbial diversity and their potential roles in diseases such as Parkinson's disease.
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Why is it important?
Accurate identification and classification of microorganisms are essential for understanding microbial diversity, ecosystem function, and disease mechanisms. This chapter provides practical bioinformatics workflows that enable researchers to analyze complex metagenomic datasets, uncover evolutionary relationships, and generate reproducible results. These approaches support advances in microbiome research, infectious disease studies, environmental monitoring, and the development of precision medicine.
Perspectives
Future advances in metagenomics will be driven by artificial intelligence, long-read sequencing, cloud computing, and multi-omics integration, enabling more accurate taxonomic and phylogenetic classification. These innovations will improve our understanding of microbial communities, accelerate biomarker discovery, and support applications in precision medicine, infectious disease surveillance, environmental monitoring, and sustainable biotechnology.
Ankit Singh Negi
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This page is a summary of: Metagenomic Taxonomic and Phylogenetic Classification, April 2026, Bentham Science Publishers,
DOI: 10.2174/9798898814502126010009.
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