Article

Evaluation of classifier performance for multiclass phenotype discrimination in untargeted metabolomics

2017-05-18

Abstract excerpt

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes and for furnishing diagnostic and prognostic phenotype predictions in medicine. Despite this, a comprehensive and rigorous evaluation of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using bo...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6f0f1ab7-111b-5f02-b5a6-ba1db63135c6
DOI: 10.1101/139584

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Evaluation of classifier performance for multiclass phenotype discrimination in untargeted metabolomicsDOI 10.1101/139584Read

Statistical analysis in metabolic phenotyping.Semantic proximity Read

Untargeted Metabolomics for Disease-Specific Signatures.Semantic proximity Read

Comparison of classification accuracy and feature selection between sparse and non-sparse modeling of metabolomics dataSemantic proximity Read

Estimation of permutation-based metabolome-wide significance thresholdsSemantic proximity Read

Machine Learning Enables Single-Score Assessment of MASLD Presence and SeveritySemantic proximity Read

Streamlining Phenotype Classification and Highlighting Feature Candidates: A Screening Method for Non-Targeted Ion Mobility Spectrometry-Mass Spectrometry (IMS-MS) Data.Semantic proximity Read

Adaptive Sparse Multi-Block PLS Discriminant Analysis: An Integrative Method for Identifying Key Biomarkers from Multi-Omics Data.Semantic proximity Read

Metabolic Profiling and the Metabolome-Wide Association Study: Significance Level For Biomarker IdentificationSemantic proximity Read

Optimized Phenotypic Biomarker Discovery and Confounder Elimination via Covariate-Adjusted Projection to Latent Structures from Metabolic Spectroscopy Data.Semantic proximity Read

A new statistical workflow (R-packages based) to investigate associations between one variable of interest and the metabolome.Semantic proximity Read

A priori sample size determination and power analysis in metabolic phenotyping and integrative metabolomics: an application framework based on a systematic review of literature.Semantic proximity Read

A Generalized Supervised Contrastive Learning Framework for Integrative Multi-omics Prediction ModelsSemantic proximity Read