Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data
暂无分享,去创建一个
Runmin Wei | Erik Jia | Tianlu Chen | Yan Ni | Jingye Wang | Mingming Su | M. Su | R. Wei | Jingye Wang | Erik Jia | Shaoqiu Chen | Tianlu Chen | Yan Ni | Shaoqiu Chen | Runmin Wei
[1] Yan Ni,et al. ADAP-GC 3.0: Improved Peak Detection and Deconvolution of Co-eluting Metabolites from GC/TOF-MS Data for Metabolomics Studies. , 2016, Analytical chemistry.
[2] Coral Barbas,et al. Missing value imputation strategies for metabolomics data , 2015, Electrophoresis.
[3] Richard D. Smith,et al. Normalization and missing value imputation for label-free LC-MS analysis , 2012, BMC Bioinformatics.
[4] Kyoungmi Kim,et al. Accounting for undetected compounds in statistical analyses of mass spectrometry ‘omic studies , 2013, Statistical applications in genetics and molecular biology.
[5] Tytus D. Mak,et al. MetaboLyzer: a novel statistical workflow for analyzing Postprocessed LC-MS metabolomics data. , 2014, Analytical chemistry.
[6] Alexander Goesmann,et al. MeltDB 2.0–advances of the metabolomics software system , 2013, Bioinform..
[7] Matej Oresic,et al. MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data , 2006, Bioinform..
[8] E. Thévenot,et al. Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses. , 2015, Journal of proteome research.
[9] Shin Ishii,et al. A Bayesian missing value estimation method for gene expression profile data , 2003, Bioinform..
[10] Xin Lu,et al. A data preprocessing strategy for metabolomics to reduce the mask effect in data analysis , 2015, Front. Mol. Biosci..
[11] Mark R. Viant,et al. Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline , 2011, Metabolomics.
[12] Trevor Hastie,et al. Imputing Missing Data for Gene Expression Arrays , 2001 .
[13] Y. Bao,et al. The ratio of dihomo‐γ‐linolenic acid to deoxycholic acid species is a potential biomarker for the metabolic abnormalities in obesity , 2017, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.
[14] David S. Wishart,et al. MetaboAnalyst 3.0—making metabolomics more meaningful , 2015, Nucleic Acids Res..
[15] Nicole A. Lazar,et al. Statistical Analysis With Missing Data , 2003, Technometrics.
[16] Joseph Hilbe,et al. Data Analysis Using Regression and Multilevel/Hierarchical Models , 2009 .
[17] A. Smilde,et al. Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation. , 2006, Analytical chemistry.
[18] Joachim Kopka,et al. TagFinder: preprocessing software for the fingerprinting and the profiling of gas chromatography-mass spectrometry based metabolome analyses. , 2012, Methods in molecular biology.
[19] David S. Wishart,et al. MetaboAnalyst: a web server for metabolomic data analysis and interpretation , 2009, Nucleic Acids Res..
[20] Yurii B. Shvetsov,et al. Circulating Unsaturated Fatty Acids Delineate the Metabolic Status of Obese Individuals , 2015, EBioMedicine.
[21] Jasper Engel,et al. Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling , 2016, Metabolomics.
[22] Piotr S. Gromski,et al. Influence of Missing Values Substitutes on Multivariate Analysis of Metabolomics Data , 2014, Metabolites.
[23] Laurent Gatto,et al. Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies. , 2016, Journal of proteome research.
[24] Russ B. Altman,et al. Missing value estimation methods for DNA microarrays , 2001, Bioinform..
[25] Roderick J. A. Little,et al. Statistical Analysis with Missing Data: Little/Statistical Analysis with Missing Data , 2002 .
[26] Joachim Selbig,et al. pcaMethods - a bioconductor package providing PCA methods for incomplete data , 2007, Bioinform..
[27] R. Abagyan,et al. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. , 2006, Analytical chemistry.
[28] Xiang Zhan,et al. Kernel approaches for differential expression analysis of mass spectrometry-based metabolomics data , 2015, BMC Bioinformatics.
[29] Ping Liu,et al. Profiling of serum bile acids in a healthy Chinese population using UPLC-MS/MS. , 2015, Journal of proteome research.
[30] T. Huan,et al. Counting missing values in a metabolite-intensity data set for measuring the analytical performance of a metabolomics platform. , 2015, Analytical chemistry.
[31] Peter Bühlmann,et al. MissForest - non-parametric missing value imputation for mixed-type data , 2011, Bioinform..
[32] B. Hammock,et al. Mass spectrometry-based metabolomics. , 2007, Mass spectrometry reviews.