Results 71 to 80 of about 17,397,740 (295)
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Model selection in linear mixed effect models
Journal of Multivariate Analysis, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Heng Peng, Ying Lu 0005
openaire +1 more source
Mixed-effects models and landscape genetic results for Hyla wrightorum.
, 2016 Mixed-effects models and landscape genetic results for Hyla wrightorum.
Caren S. Goldberg (212698) +3 more
core +1 more source
Revista Brasileira de Zootecnia, 2010 Genetic evaluations should become more accurate with the advent of whole genome selection (WGS) based on high density SNP panels. The use of WGS should then accelerate genetic gains for production traits given likely decreases in generation interval due ...
Robert John Tempelman
doaj +1 more source
FEBS Letters, EarlyView.Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley +1 more source
Novel Modelling Approaches to Characterize and Quantify Carryover Effects on Sensory Acceptability
Foods, 2018 Sensory biases caused by the residual sensations of previously served samples are known as carryover effects (COE). Contrast and convergence effects are the two possible outcomes of carryover.
Damir Dennis Torrico +5 more
doaj +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Mixed-Effects Models with Crossed Random Effects for Multivariate Longitudinal Data
, 2022 Multivariate models for longitudinal data attempt to examine change in multiple variables as well as their interrelations over time. In this study, we present a Mixed-Effects Model with Crossed Random effects (MEM-CR) for individuals and variables, and ...
José Ángel Martínez-Huertas (13834555) +1 more
core +1 more source
A variance shilf model for outlier detection and estimation in linear and linear mixed models [PDF]
, 2008 Includes abstract.Includes bibliographical references.Outliers are data observations that fall outside the usual conditional ranges of the response data.They are common in experimental research data, for example, due to transcription errors or faulty ...
Gumedze, Freedom Nkhululeko
core +1 more source
Fitting Linear Mixed-Effects Models Using lme4
Journal of Statistical Software, 2015 Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in
Douglas Bates +3 more
doaj +1 more source