Cargando…

Evaluation of linear models and missing value imputation for the analysis of peptide-centric proteomics

BACKGROUND: Several methods to handle data generated from bottom-up proteomics via liquid chromatography-mass spectrometry, particularly for peptide-centric quantification dealing with post-translational modification (PTM) analysis like reversible cysteine oxidation are evaluated. The paper proposes...

Descripción completa

Detalles Bibliográficos
Autores principales:	Berg, Philip, McConnell, Evan W., Hicks, Leslie M., Popescu, Sorina C., Popescu, George V.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2019
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419331/ https://www.ncbi.nlm.nih.gov/pubmed/30871482 http://dx.doi.org/10.1186/s12859-019-2619-6

Ejemplares similares

Missing value imputation in high-dimensional phenomic data: imputable or not, and how?
por: Liao, Serena G, et al.
Publicado: (2014)

A comparative study of evaluating missing value imputation methods in label-free proteomics
por: Jin, Liang, et al.
Publicado: (2021)

Missing value imputation in proximity extension assay-based targeted proteomics data
por: Lenz, Michael, et al.
Publicado: (2020)

Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics
por: Gardner, Miranda L., et al.
Publicado: (2021)

Missing value imputation for epistatic MAPs
por: Ryan, Colm, et al.
Publicado: (2010)

ProtRank: bypassing the imputation of missing values in differential expression analysis of proteomic data
por: Medo, Matúš, et al.
Publicado: (2019)

Assessment of label-free quantification and missing value imputation for proteomics in non-human primates
por: Hamid, Zeeshan, et al.
Publicado: (2022)

Imputation of missing genotypes: an empirical evaluation of IMPUTE
por: Zhao, Zhenming, et al.
Publicado: (2008)

Imputing missing covariate values for the Cox model
por: White, Ian R, et al.
Publicado: (2009)

The importance of batch sensitization in missing value imputation
por: Hui, Harvard Wai Hann, et al.
Publicado: (2023)

Integrative network-centric approach reveals signaling pathways associated with plant resistance and susceptibility to Pseudomonas syringae
por: Brauer, Elizabeth K., et al.
Publicado: (2018)

NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses
por: Wang, Shisheng, et al.
Publicado: (2020)

Robust imputation method for missing values in microarray data
por: Yoon, Dankyu, et al.
Publicado: (2007)

I-centric Communications
por: Arbanowski, S, et al.
Publicado: (2001)

Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
por: Seaman, Shaun R, et al.
Publicado: (2012)

Baldur: Bayesian Hierarchical Modeling for Label-Free Proteomics with Gamma Regressing Mean-Variance Trends
por: Berg, Philip, et al.
Publicado: (2023)

The phosphorylated redox proteome of Chlamydomonas reinhardtii: Revealing novel means for regulation of protein structure and function
por: McConnell, Evan W., et al.
Publicado: (2018)

The impact of imputation quality on machine learning classifiers for datasets with missing values
por: Shadbahr, Tolou, et al.
Publicado: (2023)

Using linear increment models for the imputation of missing composite outcomes in randomized trials
por: O’Keeffe, Aidan G, et al.
Publicado: (2011)

Shrinkage regression-based methods for microarray missing value imputation
por: Wang, Hsiuying, et al.
Publicado: (2013)

A hybrid imputation approach for microarray missing value estimation
por: Li, Huihui, et al.
Publicado: (2015)

A Workflow for Missing Values Imputation of Untargeted Metabolomics Data
por: Faquih, Tariq, et al.
Publicado: (2020)

Imputation of missing values for electronic health record laboratory data
por: Li, Jiang, et al.
Publicado: (2021)

Optimization methods for the imputation of missing values in Educational Institutions Data
por: Aureli, D., et al.
Publicado: (2021)

Advanced methods for missing values imputation based on similarity learning
por: Fouad, Khaled M., et al.
Publicado: (2021)

Real-time imputation of missing predictor values in clinical practice
por: Nijman, Steven W J, et al.
Publicado: (2020)

Arabidopsis thimet oligopeptidases are redox-sensitive enzymes active in the local and systemic plant immune response
por: Al-Mohanna, Thualfeqar, et al.
Publicado: (2021)

Flexible imputation of missing data
por: van Buuren, Stef
Publicado: (2018)

Missing Data and Imputation Methods
por: Schober, Patrick, et al.
Publicado: (2020)

Imputation of missing values of tumour stage in population-based cancer registration
por: Eisemann, Nora, et al.
Publicado: (2011)

Normalization and missing value imputation for label-free LC-MS analysis
por: Karpievitch, Yuliya V, et al.
Publicado: (2012)

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data
por: Wei, Runmin, et al.
Publicado: (2018)

Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets
por: Huang, Min-Wei, et al.
Publicado: (2018)

The ability of different imputation methods for missing values in mental measurement questionnaires
por: Xu, Xueying, et al.
Publicado: (2020)

Missing value imputation using least squares techniques in contaminated matrices
por: Garcia-Peña, Marisol, et al.
Publicado: (2022)

A Pragmatic Ensemble Strategy for Missing Values Imputation in Health Records
por: Batra, Shivani, et al.
Publicado: (2022)

Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
por: Zhao, Chen, et al.
Publicado: (2023)

Combining data discretization and missing value imputation for incomplete medical datasets
por: Huang, Min-Wei, et al.
Publicado: (2023)

Missing value imputation in a data matrix using the regularised singular value decomposition
por: Arciniegas-Alarcón, Sergio, et al.
Publicado: (2023)

The human communication space: towards I-centric communications
por: Arbanowski, S, et al.
Publicado: (2001)

Cannot write session to /tmp/vufind_sessions/sess_avolurrlib73f7spfsf1tc2t4l