Machine Learning For Microbial Phenotype Prediction by Roman FeldbauerMachine Learning For Microbial Phenotype Prediction by Roman Feldbauer

Machine Learning For Microbial Phenotype Prediction

byRoman Feldbauer

Paperback | June 24, 2016

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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.
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 databa...
Title:Machine Learning For Microbial Phenotype PredictionFormat:PaperbackDimensions:110 pages, 21 × 14.8 × 0.02 inPublished:June 24, 2016Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3658143185

ISBN - 13:9783658143183

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Table of Contents

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