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Published on: January 7, 2019
Signal processing for metagenomics: extracting information from the soup
Gail L Rosen1, Bahrad A Sokhansanj, Robi Polikar
1Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA, USA.
Current Genomics
|May 4, 2010
Summary
Metagenomics decodes microbial genomes from natural communities without cultivation, overcoming limitations of traditional single-genome studies. This review covers computational tools for analyzing complex metagenomic data and its applications in diverse fields.
Area of Science:
- Microbial Genomics
- Bioinformatics
- Computational Biology
Background:
- Traditional microbial genomics relies on culturable species, missing vast microbial diversity.
- Advances in sequencing and computation enable metagenomics, studying uncultured microbes in communities.
Purpose of the Study:
- Review current computational tools for metagenomic data analysis.
- Highlight applications of metagenomics in various scientific domains.
Main Methods:
- Genomic fragment annotation strategies.
- Phylogenetic reconstruction techniques for microbial communities.
- Functional classification of metagenomic samples.
- Integration of metaproteomics and metametabolomics data.
Main Results:
- Metagenomics provides insights into bacterial diversity and coding potential.
- Computational challenges in analyzing large, complex metagenomic datasets are addressed.
- Tools are available for annotation, phylogeny, and functional classification.
Conclusions:
- Metagenomics is crucial for understanding uncultured microbes and their roles.
- Addressing computational challenges is key to advancing the field.
- Metagenomic applications span microbial forensics, human health, and ecology.
