LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

Abstract Background Identification of biomarkers, which are measurable characteristics of biological datasets, can be challenging. Although amplicon sequence variants (ASVs) can be considered potential biomarkers, identifying important ASVs in high-throughput sequencing datasets is challenging. Nois...

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Bibliographic Details
Main Authors: Josip Rudar, Teresita M. Porter, Michael Wright, G. Brian Golding, Mehrdad Hajibabaei
Format: Article
Language:English
Published: BMC 2022-03-01
Series:BMC Bioinformatics
Subjects:
Biomarker selection
Metagenomics
Metabarcoding
Biomonitoring
Ecological assessment
Machine learning
Online Access:https://doi.org/10.1186/s12859-022-04631-z

Internet

https://doi.org/10.1186/s12859-022-04631-z

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