Machine learning for microbial phenotype prediction [electronic resource] / Roman Feldbauer.
2016
QH324.25
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Details
Title
Machine learning for microbial phenotype prediction [electronic resource] / Roman Feldbauer.
Author
ISBN
9783658143190 (electronic book)
3658143193 (electronic book)
9783658143183
3658143193 (electronic book)
9783658143183
Published
Wiesbaden : SpringerSpektrum, 2016.
Language
English
Language Note
In English and German.
Description
1 online resource (xiii, 110 pages) : illustrations.
Call Number
QH324.25
Dewey Decimal Classification
570.285/63
Summary
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 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". .
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed June 23, 2016).
Series
BestMasters.
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Table of Contents
Microbial Genotypes and Phenotypes
Basics of Machine Learning
Phenotype Prediction Packages
A Model for Intracellular Lifestyle.
Basics of Machine Learning
Phenotype Prediction Packages
A Model for Intracellular Lifestyle.