Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics
نویسندگان
چکیده
منابع مشابه
Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics
Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets...
متن کاملUntargeted metabolomics.
Along with genes and proteins, metabolites play important roles in sustaining life. Their functions include "primary" functions in metabolism and energy storage, as well as "secondary" functions in cell-to-cell signaling, metal acquisition, and virulence. There remains much to be learned about the in vivo roles of metabolites. Approaches that accelerate measurement of metabolite levels directly...
متن کاملTopic modeling for untargeted substructure exploration in metabolomics.
The potential of untargeted metabolomics to answer important questions across the life sciences is hindered because of a paucity of computational tools that enable extraction of key biochemically relevant information. Available tools focus on using mass spectrometry fragmentation spectra to identify molecules whose behavior suggests they are relevant to the system under study. Unfortunately, fr...
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Bottromycin A2 is a structurally unique ribosomally synthesized and post-translationally modified peptide (RiPP) that possesses potent antibacterial activity towards multidrug-resistant bacteria. The structural novelty of bottromycin stems from its unprecedented macrocyclic amidine and rare β-methylated amino acid residues. The N-terminus of a precursor peptide (BtmD) is converted into bottromy...
متن کاملUntargeted metabolomics suffers from incomplete data analysis
Introduction: Untargeted metabolomics is a powerful tool for biological discoveries. Significant advances in computational approaches to analyzing the complex raw data have been made, yet it is not clear how exhaustive and reliable are the data analysis results. Objectives: Assessment of the quality of data analysis results in untargeted metabolomics. Methods: Five published untargeted metabolo...
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ژورنال
عنوان ژورنال: Metabolites
سال: 2017
ISSN: 2218-1989
DOI: 10.3390/metabo7020030