A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Filters
GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies
[article]
2017
bioRxiv
pre-print
Preserved Fulltext
Thus, a practical left-censored missing value imputation method is urgently needed. We have developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp). ...
Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). ...
Again, GSimp performs best with the highest correlations among four
The purpose of this study is to develop a left-censored missing value imputation approach for targeted metabolomics data analysis ...
doi:10.1101/177410
fatcat:yorrdb3o35cezl243wbfxpnbii
GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies
2018
PLoS Computational Biology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Thus, a practical left-censored missing value imputation method is urgently needed. We developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp). ...
The R code for GSimp, evaluation pipeline, tutorial, real-world and simulated targeted metabolomics datasets are available at: (2018) GSimp: A Gibbs sampler based leftcensored missing value imputation ...
Peng) for their endless love and support. They are also grateful to Mr. Link who is always curious about the unexplored land. ...
doi:10.1371/journal.pcbi.1005973
pmid:29385130
pmcid:PMC5809088
fatcat:4pr66p7yafbobnm44rnko7cidm
BayesMetab: treatment of missing values in metabolomic studies using a Bayesian modeling approach
2019
BMC Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
other imputation algorithms when there is a mixture of missingness due to MAR and MNAR. ...
We develop a Bayesian model, called BayesMetab, that systematically accounts for missing values based on a Markov chain Monte Carlo (MCMC) algorithm that incorporates data augmentation by allowing MVs ...
[15] and is a MV imputation method based on left-censored (MNAR) using an iterative Gibbs sampler approach which allows flexible choice of the threshold/truncation value. ...
doi:10.1186/s12859-019-3250-2
pmid:31861984
pmcid:PMC6923847
fatcat:thc4ibnsgjgbnm7mobxsomdbcy
Missing value imputation in proximity extension assay-based targeted proteomics data
2020
PLoS ONE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Multivariate analysis of this data is hampered by frequent missing values (random or left censored), calling for imputation approaches. ...
Here, we assessed the performance of two methods for imputation of values missing completely at random, the previously top-benchmarked 'missForest' and the recently published 'GSimp' method. ...
Dorsch (Bayer AG) for project management. ...
doi:10.1371/journal.pone.0243487
pmid:33315883
fatcat:tf3h5nplc5d2rdrzyombz7rcrq
Kernel weighted least square approach for imputing missing values of metabolomics data
2021
Scientific Reports
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We developed a new kernel weight function-based proposed missing data imputation technique that resolves the problems of missing values and outliers. ...
For user convenience, an R package of the proposed kernel weight-based missing value imputation technique was developed, which is available at https://github.com/NishithPaul/tWLSA. ...
We would like to thank Editage (www. edita ge. com) for English language editing. ...
doi:10.1038/s41598-021-90654-0
pmid:34045614
fatcat:zceujfog2ngjpdpcnazkqefhum
Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
2020
International Journal of Molecular Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods ...
that have been developed to perform comprehensive analysis in proteomics studies. ...
GSimp [123] A Gibbs sampler-based left-censored missing value imputation approach for metabolomics studies. ...
doi:10.3390/ijms21082873
pmid:32326049
pmcid:PMC7216093
fatcat:5zbrkah4xvec3mq3ypal7cxfbu
Altered profiles of fecal metabolites correlate with visceral hypersensitivity and may contribute to symptom severity of diarrhea-predominant irritable bowel syndrome
2019
World Journal of Gastroenterology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Fecal metabolites, including amino acids and organic acids, were measured by targeted metabolomics approaches. Correlation analyses between these parameters were performed. ...
A possible potential biomarker panel was identified to correlate with IBS-SSS score (R 2 Adjusted = 0.693, P < 0.001). ...
Du SY for enrollment of participants. ...
doi:10.3748/wjg.v25.i43.6416
pmid:31798278
pmcid:PMC6881512
fatcat:oaxtyff25ndzzjwyf636fpg35e
Innate lymphoid cell composition associates with COVID-19 disease severity
[article]
2020
medRxiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Using supervised and unsupervised approaches, we examined the ILC activation status and homing profile. ...
Conclusion: This study provides insights into the potential role of ILCs in immune responses against SARS-CoV-2, particularly linked to the severity of COVID-19. ...
GSimp: A Gibbs sampler based left-642 censored missing value imputation approach for metabolomics studies. PLoS 643 Comput Biol 2018; 14(1). doi:10.1371/journal.pcbi.1005973 644 28. R Core Team. ...
doi:10.1101/2020.10.13.20211367
fatcat:ny3gzs4nxzh3llggdtl7tjhwmu