Results 141 to 150 of about 4,333,581 (301)
In head and neck squamous cell carcinoma (HNSCC) p53 and p63 exert opposite roles on the transcription regulation of the lncRNA NEAT1. Under basal conditions, p53 levels are low and p63 represses NEAT1 expression. Upon genotoxic stress, p53 is rapidly induced, displacing p63 from the NEAT1 promoter leading to NEAT1 transcriptional activation and ...
Sara De Domenico +5 more
wiley +1 more source
LogConcDEAD: An R Package for Maximum Likelihood Estimation of a Multivariate Log-Concave Density [PDF]
In this article we introduce the R package LogConcDEAD (Log-concave density estimation in arbitrary dimensions). Its main function is to compute the nonparametric maximum likelihood estimator of a log-concave density.
Madeleine Cule +2 more
core
Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley +1 more source
Canonical Higher-Order Kernels for Density Derivative Estimation [PDF]
In this note we present r th order kernel density derivative estimators using canonical higher-order kernels. These canonical rescalings uncouple the choice of kernel and scale factor. This approach is useful for selection of the order of the kernel in a
Christopher F. Parmeter +1 more
core
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
The Relative Improvement of Bias Reduction in Density Estimator Using Geometric Extrapolated Kernel
One of a nonparametric procedures used to estimate densities is kernel method. In this paper, in order to reduce bias of kernel density estimation, methods such as usual kernel(UK), geometric extrapolation usual kernel(GEUK), a bias reduction kernel(BRK)
Reza Salehi +2 more
doaj
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
The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R [PDF]
Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing.
Tarn Duong
core
Abruptly changing from aerobic to anaerobic conditions (sudden anaerobization) induced growth inhibition and a significant increase in intracellular labile ferrous iron in the aerotolerant anaerobe Amphibacillus xylanus. We found that free flavins mediate efficient electron transfer from NADH to ferric iron under anaerobic conditions, suggesting that ...
Shinya Kimata +13 more
wiley +1 more source

