Results 31 to 40 of about 161,037 (263)
Impact of Missing Data on Data Quality in Social Research
Соціологічні студіїMissing data is a common issue in quantitative social research that negatively affects the data quality. This article explores the consequences of missing data, outlining the potential issues it may pose and emphasizing the importance of properly ...
Yaroslav Kostenko
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Methods to Handle Incomplete Data
MAMC Journal of Medical Sciences, 2020 Context: The major question for data analysis is determining the appropriate analytic approach in the presence of incomplete observations. The most common solution to handle missing data in a data set is imputation, where missing values are estimated and
Vinny Johny +2 more
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Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
JMIR Medical Informatics, 2020 BackgroundA lifelogs-based wellness index (LWI) is a function for calculating wellness scores based on health behavior lifelogs (eg, daily walking steps and sleep times collected via a smartwatch).
Kim, Ki-Hun, Kim, Kwang-Jae
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Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
FEBS Letters, EarlyView.Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
Handling missing data in research
Perspectives in Clinical ResearchMissing data are an inevitable part of research and lead to a decrease in the size of the analyzable population, and biased and imprecise estimates. In this article, we discuss the types of missing data, methods to handle missing data and suggest ways in
Priya Ranganathan, Sally Hunsberger
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Algorithms, 2023 Ground meteorological observation data (GMOD) are the core of research on earth-related disciplines and an important reference for societal production and life.
Cong Li, Xupeng Ren, Guohui Zhao
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FEBS Letters, EarlyView.This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
Molecular Oncology, EarlyView.Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim +3 more
wiley +1 more source
Missing Data Imputation for Classification Problems
CoRR, 2020 27 pages, 5 ...
Arkopal Choudhury, Michael R. Kosorok
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