Results 71 to 80 of about 560,645 (271)

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

open access: yesFEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill   +4 more
wiley   +1 more source

OPTIMALISASI HASIL PROSES WIRE-CUT EDM DENGAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA)

open access: yesRotor: Jurnal Ilmiah Teknik Mesin, 2017
Some of the desired performance of the machining process Wire-Cut Electric Discharge Machining CV. Catur Prasetya Packindo is rate workmanship short and surface roughness of lower cutting. The problem is how to manage the performance of process variables
Mulyadi Mulyadi, Agus Puji Suryanto
doaj  

Stratification of cephalosporins based on physicochemical and pharmacokinetic variables using multivariate statistical tools

open access: yesIntelligent Pharmacy
Introduction: Cephalosporins, a class of beta-lactam antibiotics, are commonly used in medical practice. However, their potential advantages, based on physicochemical and pharmacokinetic variables, are often overlooked.
Carlos Alberto Escobar Angulo   +2 more
doaj   +1 more source

Raman Microspectral Study and Classification of the Pathological Evolution of Breast Cancer Using Both Principal Component Analysis-Linear Discriminant Analysis and Principal Component Analysis-Support Vector Machine

open access: yesJournal of Spectroscopy, 2021
To facilitate the enhanced reliability of Raman-based tumor detection and analytical methodologies, an ex vivo Raman spectral investigation was conducted to identify distinct compositional information of healthy (H), ductal carcinoma in situ (DCIS), and ...
Heping Li   +7 more
doaj   +1 more source

Quantitative proteomic analysis reveals different characteristics of bladder cancer cells after exposure to bisphenol A

open access: yesFEBS Open Bio, EarlyView.
Bisphenol A (BPA), a common chemical in plastics, exerts dual effects on bladder cancer cells: low doses promote growth and migration, while high doses suppress growth and migration. Multi‐omics and bioinformatics reveal BPA acts via MAPK and inflammatory pathways.
Shaomin Niu   +10 more
wiley   +1 more source

Uncertainty-Aware Principal Component Analysis

open access: yes, 2019
We present a technique to perform dimensionality reduction on data that is subject to uncertainty. Our method is a generalization of traditional principal component analysis (PCA) to multivariate probability distributions.
Deussen, Oliver   +4 more
core   +1 more source

Pharmacological inhibition of the PERK pathway modulates hepatocellular carcinoma growth and immune signaling

open access: yesFEBS Open Bio, EarlyView.
Pharmacological inhibition of PERK in a DEN‐induced mouse model of liver cancer does not reduce tumor burden but alters cellular stress signaling. Despite blocking PERK activity, downstream stress responses, including CHOP expression, remain active, suggesting compensatory mechanisms within the unfolded protein response that may influence tumor ...
Ada Lerma‐Clavero   +5 more
wiley   +1 more source

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

open access: yesFEBS 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   +3 more
wiley   +1 more source

On the Subspace of Image Gradient Orientations [PDF]

open access: yes, 2010
We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably
Tzimiropoulos, Georgios   +1 more
core  

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

open access: yesAnnals 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   +11 more
wiley   +1 more source

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