Results 111 to 120 of about 2,294,043 (337)
Incorporating Prior Knowledge of Principal Components in Genomic Prediction
Genomic prediction using a large number of markers is challenging, due to the curse of dimensionality as well as multicollinearity arising from linkage disequilibrium between markers.
Sayed M. Hosseini-Vardanjani +3 more
doaj +1 more source
AZD9291 has shown promise in targeted cancer therapy but is limited by resistance. In this study, we employed metabolic labeling and LC–MS/MS to profile time‐resolved nascent protein perturbations, allowing dynamic tracking of drug‐responsive proteins. We demonstrated that increased NNMT expression is associated with drug resistance, highlighting NNMT ...
Zhanwu Hou +5 more
wiley +1 more source
Spatial and multivariate analysis of soybean productivity and soil physical-chemical attributes
The objective of this study was to evaluate the spatial variability of soybean yield, carbon stock, and soil physical attributes using multivariate and geostatistical techniques.
Ricardo N. Buss +5 more
doaj +1 more source
The principal problem with principal components regression
Principal components regression (PCR) reduces a large number of explanatory variables in a regression model down to a small number of principal components.
Heidi Artigue, Gary Smith
openaire +1 more source
This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan +9 more
wiley +1 more source
On Estimation of the Noise Variance in High Dimensional Probabilistic Principal Component Analysis [PDF]
Damien Passemier +2 more
openalex +1 more source
Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology
Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts +8 more
wiley +1 more source
Mapping discourses through Hierarchical Clustering on Principal Components
This article proposes a methodological framework that combines a Q-concourse questionnaire with Multiple Factor Analysis and Hierarchical Clustering on Principal Components (MFA/HCPC) to derive discourse typologies from large-N survey data. The framework
Francesco Veri
doaj +1 more source
A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira +14 more
wiley +1 more source
Decomposing the Apoptosis Pathway Into Biologically Interpretable Principal Components
Principal component analysis (PCA) is one of the most common techniques in the analysis of biological data sets, but applying PCA raises 2 challenges. First, one must determine the number of significant principal components (PCs). Second, because each PC
Min Wang +2 more
doaj +1 more source

