Results 51 to 60 of about 202,193 (268)

Cell surface interactome analysis identifies TSPAN4 as a negative regulator of PD‐L1 in melanoma

open access: yesMolecular Oncology, EarlyView.
Using cell surface proximity biotinylation, we identified tetraspanin TSPAN4 within the PD‐L1 interactome of melanoma cells. TSPAN4 negatively regulates PD‐L1 expression and lateral mobility by limiting its interaction with CMTM6 and promoting PD‐L1 degradation.
Guus A. Franken   +7 more
wiley   +1 more source

Improved imputation of summary statistics for admixed populations [PDF]

open access: yes, 2017
AbstractMotivationSummary statistics imputation can be used to infer association summary statistics of an already conducted, genotype-based meta-analysis to higher ge-nomic resolution. This is typically needed when genotype imputation is not feasible for some cohorts.
Rüeger, Sina   +2 more
openaire   +1 more source

Handling Attrition in Longitudinal Studies: The Case for Refreshment Samples [PDF]

open access: yes, 2013
Panel studies typically suffer from attrition, which reduces sample size and can result in biased inferences. It is impossible to know whether or not the attrition causes bias from the observed panel data alone.
Deng, Yiting   +4 more
core   +2 more sources

Infrared laser sampling of low volumes combined with shotgun lipidomics reveals lipid markers in palatine tonsil carcinoma

open access: yesMolecular Oncology, EarlyView.
Nanosecond infrared laser (NIRL) low‐volume sampling combined with shotgun lipidomics uncovers distinct lipidome alterations in oropharyngeal squamous cell carcinoma (OPSCC) of the palatine tonsil. Several lipid species consistently differentiate tumor from healthy tissue, highlighting their potential as diagnostic markers.
Leonard Kerkhoff   +11 more
wiley   +1 more source

Optimal class of memory type imputation methods for time-based surveys using EWMA statistics

open access: yesScientific Reports
Time-based surveys often experience missing data due to several reasons, like non-response or data collection limitations. Imputation methods play an essential role in incorporating these missing values to secure the accuracy and reliability of the ...
Anoop Kumar   +2 more
doaj   +1 more source

Assessing uncertainty in the American Indian Trust Fund

open access: yes, 2010
Fiscal year-end balances of the Individual Indian Money System (a part of the Indian Trust) were constructed from data related to money collected in the system and disbursed by the system from 1887 to 2007.
Mulrow, Edward   +2 more
core   +1 more source

Analysis of Incomplete Compound Variables [PDF]

open access: yes, 2015
This is the peer reviewed version of the following article: Zhao, J., Cook, R. J. and Wu, C. (2015), Multiple imputation for the analysis of incomplete compound variables. Can J Statistics, 43: 240–264. doi: 10.1002/cjs.11249, which has been published in
Agresti   +33 more
core   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns   +10 more
wiley   +1 more source

Data Editing and Imputation in Business Surveys Using “R” [PDF]

open access: yesRevista Română de Statistică, 2014
Purpose – Missing data are a recurring problem that can cause bias or lead to inefficient analyses. The objective of this paper is a direct comparison between the two statistical software features R and SPSS, in order to take full advantage of the ...
Elena Romascanu
doaj  

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

open access: yesMolecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson   +9 more
wiley   +1 more source

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