Machine Learning for Microbial Phenotype Prediction

Name: Machine Learning for Microbial Phenotype Prediction
Brand: Springer
SKU: 9783658143183
Price: 3639.0 INR
Availability: InStock

by Roman Feldbauer

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ISBN13: 9783658143183
Binding: Paperback
Subject: N/A
Publisher: Springer
Publisher Imprint: Springer Spektrum
Publication Date: June 24, 2016
Pages: 110
Original Price: EUR 49.99
Language: English
Edition: 2016
Item Weight: 170 grams
BISAC Subject(s): Life Sciences / Anatomy & Physiology, Applied, and Life Sciences / Microbiology

About The Book

From the Back Cover
This thesis presents a scalable, generic methodology for microbial phenotype prediction based on supervised machine learning, several models for biological and ecological traits of high relevance, and the deployment in metagenomic datasets. The results suggest that the presented prediction tool can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomic studies. Unraveling relationships between a living organism's genetic information and its observable traits is a central biological problem. Phenotype prediction facilitated by machine learning techniques will be a major step forward to creating biological knowledge from big data.
Contents

Microbial Genotypes and Phenotypes
Basics of Machine Learning
Phenotype Prediction Packages
A Model for Intracellular Lifestyle

Target Groups

Teachers and students in the fields of bioinformatics, molecular biology and microbiology

Executives and specialists in the field of microbiology, computational biology and machine learning

About the AuthorRoman Feldbauer is currently employed at the Austrian Research Institute for Artificial Intelligence (OFAI) and PhD student at the University of Vienna. His research interests are machine learning, data science, bioinformatics, comparative genomics and neuroscience. In one of his current projects he investigates large biological databases in regard to the "curse of dimensionality."

About The Author

Roman Feldbauer is currently employed at the Austrian Research Institute for Artificial Intelligence (OFAI) and PhD student at the University of Vienna. His research interests are machine learning, data science, bioinformatics, comparative genomics and neuroscience. In one of his current projects he investigates large biological databases in regard to the "curse of dimensionality".

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