Using Machine Learning as Decision Making for Microbiome Data
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Descripción
The new technologies that have been developed and used in the last few decades have enabled generation of vast amount of data. The existing and developing computing techniques are being used to analyze and interpret this data and enable better decision making.
This book summarizes the computational techniques that have been applied to the genetic data that consists of strings of four nucleotides and, in particular, to the data that describes microbe genetics. The next generation sequencing techniques have enabled us to determine the strings of nucleotides that describe either the whole genome or particular regions of RNA and DNA.
Microbiome is collection of microorganisms that live in a particular environment. The data that has been explored in this book comes from the human gut habitat. In particular, we have explored data that describes bacterial makeup of human gut samples. The difference in this makeup has been linked in the current literature with the number of conditions, diseases, and other describing factors of humans (such as diet, age, gender etc.).