Microbiome Data: Bioinformatic, Computational and Statistical Analysis - by Gianni Russell (Hardcover)

About the Book

Microbiome data comprises the genetic material of all the microorganisms in a specific environment, such as the human gut, soil, or ocean. This data is crucial for understanding the complex interactions between microorganisms and their hosts or environments. It typically includes information obtained through high-throughput sequencing technologies like 16S rRNA gene sequencing, metagenomics, and metatranscriptomics. Analyzing microbiome data can reveal insights into microbial diversity, community structure, and functional capabilities. This has significant implications for fields such as medicine, agriculture, and environmental science. For instance, in human health, microbiome data helps in identifying links between microbial communities and diseases, leading to potential diagnostic and therapeutic advancements. In agriculture, it aids in enhancing soil health and crop productivity. This book elucidates the concepts and innovative models around prospective developments with respect to bioinformatic, computational and statistical analysis of microbiome data. It strives to provide a fair idea about this discipline and to help develop a better understanding of the latest advances within this field. The readers would gain knowledge that would broaden their perspective about microbiome data.

Book Synopsis

Microbiome data comprises the genetic material of all the microorganisms in a specific environment, such as the human gut, soil, or ocean. This data is crucial for understanding the complex interactions between microorganisms and their hosts or environments. It typically includes information obtained through high-throughput sequencing technologies like 16S rRNA gene sequencing, metagenomics, and metatranscriptomics. Analyzing microbiome data can reveal insights into microbial diversity, community structure, and functional capabilities. This has significant implications for fields such as medicine, agriculture, and environmental science. For instance, in human health, microbiome data helps in identifying links between microbial communities and diseases, leading to potential diagnostic and therapeutic advancements. In agriculture, it aids in enhancing soil health and crop productivity. This book elucidates the concepts and innovative models around prospective developments with respect to bioinformatic, computational and statistical analysis of microbiome data. It strives to provide a fair idea about this discipline and to help develop a better understanding of the latest advances within this field. The readers would gain knowledge that would broaden their perspective about microbiome data.