Machine Learning for Microbial Phenotype Prediction (BestMasters) - Couverture souple

Feldbauer, Roman

Couverture souple

ISBN 10 : 3658143185 ISBN 13 : 9783658143183

Editeur : Springer Spektrum, 2016

Synopsis

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.

A propos du livre

À propos de l?auteur

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“.

À propos de la quatrième de couverture

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 . 

Détails de l'édition

• Éditeur: Springer Spektrum
• Date d'édition: 2016
• Langue: anglais
• ISBN 10: 3658143185
• ISBN 13: 9783658143183
• Reliure: Tapa blanda
• Numéro d'édition: 1
• Nombre de pages: 124
• Coordonnées du fabricant: non disponible
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