Results 71 to 80 of about 415,661 (284)

Early‐life high‐fat diet exposure increases Achilles tendon stiffness and induces transcriptomic alterations

FEBS Open Bio, EarlyView.
Early‐life exposure to a high‐fat diet altered intact Achilles tendons in rat offspring, making them thinner, stiffer, and molecularly distinct even without injury. These findings suggest that developmental high‐fat diet exposure may impair tendon quality and increase susceptibility to mechanical overload or tendon injury later in life.
Heyong Yin, Ziyang Yuan, Wenli Jiang, Ai Guo   +3 more
wiley   +1 more source

randPedPCA: rapid approximation of principal components from large pedigrees

Genetics Selection Evolution
Background Pedigrees continue to be extremely important in agriculture and conservation genetics, with the pedigrees of modern breeding programmes easily comprising millions of records.
Hanbin Lee, Rosalind Françoise Craddock, Gregor Gorjanc, Hannes Becher   +3 more
doaj   +1 more source

Biplots for compositional data derived from generalized joint diagonalization methods

Applied Computing and Geosciences, 2020
Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors ...
U. Mueller, R. Tolosana Delgado, E.C. Grunsky, J.M. McKinley   +3 more
doaj   +1 more source

PEMODELAN PERSENTASE BALITA GIZI BURUK DI JAWA TENGAH DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION PRINCIPAL COMPONENTS ANALYSIS (GWRPCA) [PDF]

, 2015
Geographically Weighted Regression Principal Components Analysis (GWRPCA) is a combination of method of Principal Components Analysis (PCA) and Geographically Weighted Regression (GWR).
PRATNYANINGRUM, NOVIKA
core  

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Ensemble Principal Component Analysis

IEEE Access
Efficient representations of data are essential for processing, exploration, and human understanding, and Principal Component Analysis (PCA) is one of the most common dimensionality reduction techniques used for the analysis of large, multivariate ...
Olga Dorabiala, Aleksandr Y. Aravkin, J. Nathan Kutz   +2 more
doaj   +1 more source

An example of using obliquely rotated principal components to detect circulation types over Europe

Meteorologische Zeitschrift, 1993
Principal component analysis (PCA) is applied to selected gridded 500 hPa height data over Europe, the stratification of which is known in advance, in order to evaluate its ability to find dominating circulation types.
Radan Huth
doaj   +1 more source

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source

PEMBUATAN PERANGKAT LUNAK PENGENALAN WAJAH MENGGUNAKAN PRINCIPAL COMPONENTS ANALYSIS

Jurnal Informatika, 2001
Face recognition is one of many important researches, and today, many applications have implemented it. Through development of techniques like Principal Components Analysis (PCA), computers can now outperform human in many face recognition tasks ...
Kartika Gunadi, Sonny Reinard Pongsitanan   +1 more
doaj  

An Infinitesimal Probabilistic Model for Principal Component Analysis of Manifold Valued Data

, 2018
We provide a probabilistic and infinitesimal view of how the principal component analysis procedure (PCA) can be generalized to analysis of nonlinear manifold valued data. Starting with the probabilistic PCA interpretation of the Euclidean PCA procedure,
Sommer, Stefan
core   +1 more source