Results 81 to 90 of about 17,397,225 (294)
Stochastic Differential Mixed-Effects Models
Scandinavian Journal of Statistics, 2010 Continuous processes \(X_t^i\) are observed for \(M\) different experimental units \(i=1,\dots,M\) at discrete time points. The stochastic differential mixed effect model (SDMEM) assumes that \[ dX_t^i=\mu(X_t^i,\vartheta,b^i)dt+\sigma(X_t^i,\vartheta,b^i)dw_t^i, \] where \(w_t^i\) are standard Brownian motions, \(\mu\) and \(\sigma\) are known drift ...
Picchini U, De Gaetano A, Ditlevsen S
openaire +6 more sources
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Mixed Effects Analysis of Height Growth in Ethiopian Children Aged 1-12 Years: A Cohort Study
East African Journal of Biophysical and Computational SciencesModelling physical growth is a key component to examine and identify definingcharacteristics in the growth process.The goal of this study was to model and captureknown features of height growth in Ethiopian children aged 1–12 years.
Dereje Danbe Debeko, Ayele Taye Goshu
doaj +2 more sources
How to become twice more precise in detecting neuropsychological impairments
Frontiers in Psychology, 2014 Introduction Although it was a giant leap forward when it was introduced, the classic approach to the norming of neuropsychological tests (Capitani, 1987) has two main limitations: (i) it doesn’t consider possible interactions between covariates (e.g ...
Davide Crepaldi +4 more
doaj +1 more source
Robust Classification of Functional and Quantitative Image Data Using Functional Mixed Models [PDF]
, 2012 This paper describes how to perform classification of complex, high-dimensional functional data using the functional mixed model (FMM) framework. The FMM relates a functional response to a set of predictors through functional fixed and random effects ...
Morris, Jeffrey S. +5 more
core +1 more source
Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions
FEBS Letters, EarlyView.The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang +4 more
wiley +1 more source
Education SciencesInternational literature has documented a sustained increase in female representation in higher education; however, less is known about how this process unfolds in segmented and highly privatized systems such as Chile’s.
Ana Moraga-Pumarino +4 more
doaj +1 more source
One Direction? A Tutorial for Circular Data Analysis Using R With Examples in Cognitive Psychology
Frontiers in Psychology, 2018 Circular data is data that is measured on a circle in degrees or radians. It is fundamentally different from linear data due to its periodic nature (0° = 360°). Circular data arises in a large variety of research fields.
Jolien Cremers, Irene Klugkist
doaj +1 more source
Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential
FEBS Letters, EarlyView.Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta +3 more
wiley +1 more source