Current opportunities and challenges in microbial metagenome analysis--a bioinformatic perspective
- PMID: 22966151
- PMCID: PMC3504927
- DOI: 10.1093/bib/bbs039
Current opportunities and challenges in microbial metagenome analysis--a bioinformatic perspective
Abstract
Metagenomics has become an indispensable tool for studying the diversity and metabolic potential of environmental microbes, whose bulk is as yet non-cultivable. Continual progress in next-generation sequencing allows for generating increasingly large metagenomes and studying multiple metagenomes over time or space. Recently, a new type of holistic ecosystem study has emerged that seeks to combine metagenomics with biodiversity, meta-expression and contextual data. Such 'ecosystems biology' approaches bear the potential to not only advance our understanding of environmental microbes to a new level but also impose challenges due to increasing data complexities, in particular with respect to bioinformatic post-processing. This mini review aims to address selected opportunities and challenges of modern metagenomics from a bioinformatics perspective and hopefully will serve as a useful resource for microbial ecologists and bioinformaticians alike.
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References
-
- Gans J, Wolinsky M, Dunbar J. Computational improvements reveal great bacterial diversity and high metal toxicity in soil. Science. 2005;309(5739):1387–90. - PubMed