Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data (Q31148892)

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English	Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data	scientific article

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scholarly article

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Europe PubMed Central

29 June 2017

Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data (English)

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Europe PubMed Central

29 June 2017

feature selection

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based on heuristic

inferred from title

author name string

David P Enot

1

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Europe PubMed Central

29 June 2017

Wanchang Lin

2

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Europe PubMed Central

29 June 2017

Manfred Beckmann

3

1 reference

Europe PubMed Central

29 June 2017

David Parker

4

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Europe PubMed Central

29 June 2017

David P Overy

5

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Europe PubMed Central

29 June 2017

John Draper

6

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Europe PubMed Central

29 June 2017

publication date

1 January 2008

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Europe PubMed Central

29 June 2017

Nature Protocols

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Europe PubMed Central

29 June 2017

3

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Europe PubMed Central

29 June 2017

446-470

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Europe PubMed Central

29 June 2017

3

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Europe PubMed Central

29 June 2017

Data-adaptive test statistics for microarray data

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Class prediction and discovery using gene microarray and proteomics mass spectroscopy data: curses, caveats, cautions

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Avoiding model selection bias in small-sample genomic datasets.

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Is cross-validation valid for small-sample microarray classification?

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Statistical strategies for avoiding false discoveries in metabolomics and related experiments

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Global strategies to integrate the proteome and metabolome

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Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer

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What should be expected from feature selection in small-sample settings.

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Predicting interpretability of metabolome models based on behavior, putative identity, and biological relevance of explanatory signals

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Genomic computing. Explanatory analysis of plant expression profiling data using machine learning

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Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops

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Metabolomics by numbers: acquiring and understanding global metabolite data

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Potential of metabolomics as a functional genomics tool.

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Metabolite profiling for plant functional genomics

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Plant metabolomics: large-scale phytochemistry in the functional genomics era.

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Simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry

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Analysis of highly polar compounds of plant origin: combination of hydrophilic interaction chromatography and electrospray ion trap mass spectrometry.

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Representation, comparison, and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars

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Ultra-performance liquid chromatography coupled to linear ion trap mass spectrometry for the identification of drug metabolites in biological samples

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Construction and application of a mass spectral and retention time index database generated from plant GC/EI-TOF-MS metabolite profiles

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A strategy for identifying differences in large series of metabolomic samples analyzed by GC/MS.

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Assessment of 1H NMR spectroscopy and multivariate analysis as a technique for metabolite fingerprinting of Arabidopsis thaliana

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High-throughput classification of yeast mutants for functional genomics using metabolic footprinting.

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Metabolite fingerprinting: detecting biological features by independent component analysis.

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Nontargeted metabolome analysis by use of Fourier Transform Ion Cyclotron Mass Spectrometry

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Measuring the metabolome: current analytical technologies

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High-throughput, nontargeted metabolite fingerprinting using nominal mass flow injection electrospray mass spectrometry

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Explanatory signal interpretation and metabolite identification strategies for nominal mass FIE-MS metabolite fingerprints

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Rice blast infection of Brachypodium distachyon as a model system to study dynamic host/pathogen interactions

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Rules of evidence for cancer molecular-marker discovery and validation

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Reliable gene signatures for microarray classification: assessment of stability and performance.

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Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data

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Scaling and normalization effects in NMR spectroscopic metabonomic data sets

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ROCR: visualizing classifier performance in R

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Estimating misclassification error with small samples via bootstrap cross-validation.

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Identifying Important Risk Factors for Survival in Kidney Graft Failure Patients Using Random Survival Forests

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Flow-injection electrospray ionization mass spectrometry of crude cell extracts for high-throughput bacterial identification

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Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems

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Use of electrospray ionization mass spectrometry for profiling of crude oil effects on the phospholipid molecular species of two marine bacteria.

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Monitoring the production yields of vincristine and vinblastine in Catharanthus roseus from somatic embryogenesis. Semiquantitative determination by flow-injection electrospray ionization mass spectrometry

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Application of metabolite profiling to the identification of traits in a population of tomato introgression lines

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Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry.

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High-throughput direct-infusion ion trap mass spectrometry: a new method for metabolomics

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A direct approach to false discovery rates

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10.1038/NPROT.2007.511

1 reference

Europe PubMed Central

29 June 2017

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Europe PubMed Central

29 June 2017

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Springer Nature article ID

10.1038/nprot.2007.511

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