Machine Learning Models for Error Detection in Metagenomics and Polyploid Sequencing Data

Machine Learning Models for Error Detection in Metagenomics and Polyploid Sequencing Data

Metagenomics studies, as well as genomics studies of polyploid species such as wheat, deal with the analysis of high variation data. Such data contain sequences from similar, but distinct genetic chains. This fact presents an obstacle to analysis and research. In particular, the detection of instrum...

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Bibliographic Details
Main Authors: Milko Krachunov, Maria Nisheva, Dimitar Vassilev
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Information
Subjects:
machine learning
neural network
NGS errors
metagenomics
polyploid genomes
Online Access:http://www.mdpi.com/2078-2489/10/3/110

Internet

http://www.mdpi.com/2078-2489/10/3/110

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