Results 21 to 30 of about 230,992 (300)

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

open access: yesFrontiers in Genetics, 2021
The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics.
Venceslas Douillard   +8 more
doaj   +1 more source

Next-generation genotype imputation service and methods

open access: yesNature Genetics, 2016
Genotype imputation is a key component of genetic association studies, where it increases power, facilitates meta-analysis, and aids interpretation of signals.
Sayantani Das   +20 more
semanticscholar   +1 more source

Optimizing Selection of the Reference Population for Genotype Imputation From Array to Sequence Variants

open access: yesFrontiers in Genetics, 2019
Imputation of high-density genotypes to whole-genome sequences (WGS) is a cost-effective method to increase the density of available markers within a population.
Adrien M. Butty   +9 more
doaj   +1 more source

Improving Cardiovascular Disease Prediction by Integrating Imputation, Imbalance Resampling, and Feature Selection Techniques into Machine Learning Model

open access: yesIJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023
Cardiovascular disease (CVD) is the leading cause of death worldwide. Primary prevention is by early prediction of the disease onset. Using laboratory data from the National Health and Nutrition Examination Survey (NHANES) in 2017-2020 timeframe (N= 7 ...
Fadlan Hamid Alfebi, Mila Desi Anasanti
doaj   +1 more source

A ‘Chief Error’ of Protestant Soteriology: Sin in the Justified and Early Modern Catholic Theology

open access: yesPerichoresis: The Theological Journal of Emanuel University, 2020
Catholic theologians after Trent saw the Protestant teaching about the remnants of original sin in the justified as one of the ‘chief ’ errors of Protestant soteriology.
Gaetano Matthew T.
doaj   +1 more source

HyperImpute: Generalized Iterative Imputation with Automatic Model Selection [PDF]

open access: yesInternational Conference on Machine Learning, 2022
Consider the problem of imputing missing values in a dataset. One the one hand, conventional approaches using iterative imputation benefit from the simplicity and customizability of learning conditional distributions directly, but suffer from the ...
Daniel Jarrett   +4 more
semanticscholar   +1 more source

Enhancing water use efficiency in precision irrigation: data-driven approaches for addressing data gaps in time series

open access: yesFrontiers in Water, 2023
Real-time soil matric potential measurements for determining potato production's water availability are currently used in precision irrigation. It is well known that managing irrigation based on soil matric potential (SMP) helps increase water use ...
Mohammad Zeynoddin   +2 more
doaj   +1 more source

To Impute or Not To Impute in Untargeted Metabolomics─That is the Compositional Question [PDF]

open access: yesJournal of the American Society for Mass Spectrometry
ABSTRACT Untargeted metabolomics often produce large datasets with missing values, arising from biological or technical factors, which can undermine statistical analyses and lead to biased biological interpretations. Imputation methods, such as k-Nearest Neighbors (kNN) and Random Forest (RF) regression are commonly used but their ...
Dennis Dimitri Krutkin   +6 more
openaire   +2 more sources

Comparing Methods to Select Candidates for Re-Genotyping to Impute Higher-Density Genotype Data in a Japanese Black Cattle Population: A Case Study

open access: yesAnimals, 2023
As optimization methods to identify the best animals for dense genotyping to construct a reference population for genotype imputation, the MCA and MCG methods, which use the pedigree-based additive genetic relationship matrix (A matrix) and the genomic ...
Shinichiro Ogawa   +3 more
doaj   +1 more source

MICE: Multivariate Imputation by Chained Equations in R

open access: yes, 2011
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package.
S. Buuren, K. Groothuis-Oudshoorn
semanticscholar   +1 more source

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