Results 71 to 80 of about 408,145 (290)

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

open access: yesFEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei   +3 more
wiley   +1 more source

Image encoding by independent principal components [PDF]

open access: yes, 2010
The encoding of images by semantic entities is still an unresolved task. This paper proposes the encoding of images by only a few important components or image primitives. Classically, this can be done by the Principal Component Analysis (PCA). Recently,
Arlt, Björn, Brause, Rüdiger W.
core  

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

open access: yes, 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

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

open access: yesFEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes   +32 more
wiley   +1 more source

Insights Into the Antigenic Repertoire of Unclassified Synaptic Antibodies

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective We sought to characterize the sixth most common finding in our neuroimmunological laboratory practice (tissue assay‐observed unclassified neural antibodies [UNAs]), combining protein microarray and phage immunoprecipitation sequencing (PhIP‐Seq). Methods Patient specimens (258; 133 serums; 125 CSF) meeting UNA criteria were profiled;
Michael Gilligan   +22 more
wiley   +1 more source

randPedPCA: rapid approximation of principal components from large pedigrees

open access: yesGenetics 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   +3 more
doaj   +1 more source

Biplots for compositional data derived from generalized joint diagonalization methods

open access: yesApplied 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   +3 more
doaj   +1 more source

Basilar Artery Occlusion Stroke Managed With Tenecteplase Versus Alteplase Before Endovascular Treatment (BAO‐TNK)

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To compare the effectiveness and safety of tenecteplase (TNK) versus alteplase (TPA) in patients with basilar artery occlusion prior to endovascular treatment (EVT). Methods In this retrospective multicenter study (BAO‐TNK), we analyzed consecutive BAO patients from 14 U.S.
Rahul R. Karamchandani   +38 more
wiley   +1 more source

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

open access: yes, 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

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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