(Download) "Metagenomics for Microbiology" by Jacques Izard & Maria Rivera " Book PDF Kindle ePub Free
eBook details
- Title: Metagenomics for Microbiology
- Author : Jacques Izard & Maria Rivera
- Release Date : January 07, 2014
- Genre: Biology,Books,Science & Nature,Life Sciences,Professional & Technical,Medical,
- Pages : * pages
- Size : 10835 KB
Description
Concisely discussing the application of high throughput analysis to move forward our understanding of microbial principles, Metagenomics for Microbiology provides a solid base for the design and analysis of omics studies for the characterization of microbial consortia. The intended audience includes clinical and environmental microbiologists, molecular biologists, infectious disease experts, statisticians, biostatisticians, and public health scientists. This book focuses on the technological underpinnings of metagenomic approaches and their conceptual and practical applications.
With the next-generation genomic sequencing revolution increasingly permitting researchers to decipher the coding information of the microbes living with us, we now have a unique capacity to compare multiple sites within individuals and at higher resolution and greater throughput than hitherto possible. The recent articulation of this paradigm points to unique possibilities for investigation of our dynamic relationship with these cellular communities, and excitingly the probing of their therapeutic potential in disease prevention or treatment of the future.
Expertly describes the latest metagenomic methodologies and best-practices, from sample collection to data analysis for taxonomic, whole shotgun metagenomic, and metatranscriptomic studiesIncludes clear-headed pointers and quick starts to direct research efforts and increase study efficacy, eschewing ponderous prosePresented topics include sample collection and preparation, data generation and quality control, third generation sequencing, advances in computational analyses of shotgun metagenomic sequence data, taxonomic profiling of shotgun data, hypothesis testing, and mathematical and computational analysis of longitudinal data and time series. Past-examples and prospects are provided to contextualize the applications.
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