Binary Classification of Metagenomic Samples Using Discriminative DNA Superstrings

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00225580" target="_blank" >RIV/68407700:21230/14:00225580 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Binary Classification of Metagenomic Samples Using Discriminative DNA Superstrings
Original language description
Increasing amount of data obtained by the NGS technologies increases the urge of effective analysis of this data. This work presents a tool for binary classification of metagenomic samples. Metagenomic samples consist of a large amount of short DNA strings (also called reads), which belong to different organisms present in an environ- ment from which the sample was taken. Behavior of an environment can be affected by the contamination by the organisms, which originaly do not belong in this envi- ronment. The goal of this work is to develop a classification method based on DNA superstrings that can accurately classify metagenomic samples. Classifiers obtained by this method can be used for determining whether newly obtained metagenomic samples are contaminated (positive) or clean (negative) without the need of identifi- cation of particular organisms present in the sample. We want to achieve this goal by establishing a modified sequence assembly task for finding the most discriminatory
Czech name
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Czech description
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Project
<a href="/en/project/GAP202%2F12%2F2032" target="_blank" >GAP202/12/2032: Predicting protein properties through spatial statistical relational machine learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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