147 related articles for article (PubMed ID: 36810890)
1. The importance of batch sensitization in missing value imputation.
Hui HWH; Kong W; Peng H; Goh WWB
Sci Rep; 2023 Feb; 13(1):3003. PubMed ID: 36810890
[TBL] [Abstract][Full Text] [Related]
2. How missing value imputation is confounded with batch effects and what you can do about it.
Goh WWB; Hui HWH; Wong L
Drug Discov Today; 2023 Sep; 28(9):103661. PubMed ID: 37301250
[TBL] [Abstract][Full Text] [Related]
3. Dealing with missing values in proteomics data.
Kong W; Hui HWH; Peng H; Goh WWB
Proteomics; 2022 Dec; 22(23-24):e2200092. PubMed ID: 36349819
[TBL] [Abstract][Full Text] [Related]
4. ProJect: a powerful mixed-model missing value imputation method.
Kong W; Wong BJH; Hui HWH; Lim KP; Wang Y; Wong L; Goh WWB
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37419612
[TBL] [Abstract][Full Text] [Related]
5. Multiple imputation with sequential penalized regression.
Zahid FM; Heumann C
Stat Methods Med Res; 2019 May; 28(5):1311-1327. PubMed ID: 29451087
[TBL] [Abstract][Full Text] [Related]
6. Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework.
Voillet V; Besse P; Liaubet L; San Cristobal M; González I
BMC Bioinformatics; 2016 Oct; 17(1):402. PubMed ID: 27716030
[TBL] [Abstract][Full Text] [Related]
7. DNA microarray data imputation and significance analysis of differential expression.
Jörnsten R; Wang HY; Welsh WJ; Ouyang M
Bioinformatics; 2005 Nov; 21(22):4155-61. PubMed ID: 16118262
[TBL] [Abstract][Full Text] [Related]
8. Review of Batch Effects Prevention, Diagnostics, and Correction Approaches.
Čuklina J; Pedrioli PGA; Aebersold R
Methods Mol Biol; 2020; 2051():373-387. PubMed ID: 31552638
[TBL] [Abstract][Full Text] [Related]
9. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
[TBL] [Abstract][Full Text] [Related]
10. MissForest--non-parametric missing value imputation for mixed-type data.
Stekhoven DJ; Bühlmann P
Bioinformatics; 2012 Jan; 28(1):112-8. PubMed ID: 22039212
[TBL] [Abstract][Full Text] [Related]
11. A Simple Optimization Workflow to Enable Precise and Accurate Imputation of Missing Values in Proteomic Data Sets.
Dabke K; Kreimer S; Jones MR; Parker SJ
J Proteome Res; 2021 Jun; 20(6):3214-3229. PubMed ID: 33939434
[TBL] [Abstract][Full Text] [Related]
12. Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies.
Lazar C; Gatto L; Ferro M; Bruley C; Burger T
J Proteome Res; 2016 Apr; 15(4):1116-25. PubMed ID: 26906401
[TBL] [Abstract][Full Text] [Related]
13. Missing value imputation strategies for metabolomics data.
Armitage EG; Godzien J; Alonso-Herranz V; López-Gonzálvez Á; Barbas C
Electrophoresis; 2015 Dec; 36(24):3050-60. PubMed ID: 26376450
[TBL] [Abstract][Full Text] [Related]
14. BIRCH: An Automated Workflow for Evaluation, Correction, and Visualization of Batch Effect in Bottom-Up Mass Spectrometry-Based Proteomics Data.
Sundararaman N; Bhat A; Venkatraman V; Binek A; Dwight Z; Ariyasinghe NR; Escopete S; Joung SY; Cheng S; Parker SJ; Fert-Bober J; Van Eyk JE
J Proteome Res; 2023 Feb; 22(2):471-481. PubMed ID: 36695565
[TBL] [Abstract][Full Text] [Related]
15. An integrative imputation method based on multi-omics datasets.
Lin D; Zhang J; Li J; Xu C; Deng HW; Wang YP
BMC Bioinformatics; 2016 Jun; 17():247. PubMed ID: 27329642
[TBL] [Abstract][Full Text] [Related]
16. Missing value imputation in proximity extension assay-based targeted proteomics data.
Lenz M; Schulz A; Koeck T; Rapp S; Nagler M; Sauer M; Eggebrecht L; Ten Cate V; Panova-Noeva M; Prochaska JH; Lackner KJ; Münzel T; Leineweber K; Wild PS; Andrade-Navarro MA
PLoS One; 2020; 15(12):e0243487. PubMed ID: 33315883
[TBL] [Abstract][Full Text] [Related]
17. Evaluating Imputation Algorithms for Low-Depth Genotyping-By-Sequencing (GBS) Data.
Chan AW; Hamblin MT; Jannink JL
PLoS One; 2016; 11(8):e0160733. PubMed ID: 27537694
[TBL] [Abstract][Full Text] [Related]
18. Examining the practical limits of batch effect-correction algorithms: When should you care about batch effects?
Zhou L; Chi-Hau Sue A; Bin Goh WW
J Genet Genomics; 2019 Sep; 46(9):433-443. PubMed ID: 31611172
[TBL] [Abstract][Full Text] [Related]
19. Tools for statistical analysis with missing data: application to a large medical database.
Preda C; Duhamel A; Picavet M; Kechadi T
Stud Health Technol Inform; 2005; 116():181-6. PubMed ID: 16160256
[TBL] [Abstract][Full Text] [Related]
20. Advanced bioinformatics methods for practical applications in proteomics.
Goh WWB; Wong L
Brief Bioinform; 2019 Jan; 20(1):347-355. PubMed ID: 30657890
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]