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Books > Science & Mathematics > Biology, life sciences > Microbiology (non-medical)

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Machine Learning for Microbial Phenotype Prediction (Paperback, 1st ed. 2016) Loot Price: R1,635
Discovery Miles 16 350
Repayment Terms: R153 pm x 12*
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Machine Learning for Microbial Phenotype Prediction (Paperback, 1st ed. 2016): Roman Feldbauer

Machine Learning for Microbial Phenotype Prediction (Paperback, 1st ed. 2016)

Roman Feldbauer

Series: BestMasters

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Loot Price R1,635 Discovery Miles 16 350 | Repayment Terms: R153 pm x 12*

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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.

General

Imprint: Springer Spektrum
Country of origin: Germany
Series: BestMasters
Release date: June 2016
First published: 2016
Authors: Roman Feldbauer
Dimensions: 210 x 148 x 7mm (L x W x T)
Format: Paperback
Pages: 110
Edition: 1st ed. 2016
ISBN-13: 978-3-658-14318-3
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Science & Mathematics > Biology, life sciences > Microbiology (non-medical) > General
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LSN: 3-658-14318-5
Barcode: 9783658143183

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