Results 91 to 100 of about 16,379,393 (306)

D-Optimal designs for a multivariate regression model

open access: yesJournal of Multivariate Analysis, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Krafft, Olaf, Schaefer, Martin
openaire   +2 more sources

RANCANGAN D-OPTIMAL MODEL MICHAELIS MENTEN DAN EMAX DENGAN MATLAB

open access: yesMedia Statistika, 2015
Michaelis Menten and Emax models  are  widely used in chemistry, pharmacokinetics and pharmacodynamics areas. D-optimal criteria is criteria with the purpuse to minimize the variance of the estimator of parameters in the model. In this paper will discuss
Tatik Widiharih   +3 more
doaj   +1 more source

Golgi enzymes are retrieved from the plasma membrane to the trans‐Golgi network

open access: yesFEBS Letters, EarlyView.
Golgi enzymes are traditionally considered resident proteins retained within the Golgi apparatus. Here, we demonstrate that a subset transiently reaches the cell surface and is subsequently retrieved to the trans‐Golgi network via retrograde transport. Using a nanobody‐based toolkit, we uncover a dynamic trafficking cycle of several Golgi enzymes.
Dominik P. Buser, Tina Junne
wiley   +1 more source

Optimal discrimination designs [PDF]

open access: yes
We consider the problem of constructing optimal designs for model discrimination between competing regression models. Various new properties of optimal designs with respect to the popular T-optimality criterion are derived, which in many circumstances ...
Dette, Holger, Titoff, Stefanie
core  

Partial depletion of plasminogen activator inhibitor‐1 decreases subcutaneous fat cell hypertrophy and liver cholesterol in high‐fat‐fed female mice

open access: yesFEBS Letters, EarlyView.
Obesity raises blood levels of PAI‐1, a protein linked to metabolic dysfunction‐associated steatotic liver disease in people with obesity. In female mice fed a high‐fat diet, partially lowering PAI‐1 led to smaller subcutaneous fat cells and lower liver cholesterol, without changing body weight or insulin sensitivity.
Claudia E. Ramirez Bustamante   +10 more
wiley   +1 more source

Simulations on the Combinatorial Structure of D-Optimal Designs [PDF]

open access: yes, 2018
In this work we present the results of several simulations on main-effect factorial designs. The goal of such simulations is to investigate the connections between the $D$-optimality of a design and its geometrical structure. By means of a combinatorial object, namely the circuit basis of the design matrix, we show that it is possible to define a ...
Roberto Fontana, Fabio Rapallo
openaire   +5 more sources

Bayesian and maximin optimal designs for heteroscedastic regression models [PDF]

open access: yes
The problem of constructing standardized maximin D-optimal designs for weighted polynomial regression models is addressed. In particular it is shown that, by following the broad approach to the construction of maximin designs introduced recently by Dette,
Dette, Holger   +2 more
core  

Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry

open access: yesFEBS Letters, EarlyView.
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri   +5 more
wiley   +1 more source

Optimal Discrimination Designs for Exponential Regression Models [PDF]

open access: yes
We investigate optimal designs for discriminating between exponential regression models of different complexity, which are widely used in the biological sciences; see, e.g., Landaw (1995) or Gibaldi and Perrier (1982). We discuss different approaches for
Dette, Holger   +2 more
core  

On optimal designs for nonlinear models: a general and efficient algorithm

open access: yes, 2013
Deriving optimal designs for nonlinear models is challenging in general. Although some recent results allow us to focus on a simple subclass of designs for most problems, deriving a specific optimal design mainly depends on algorithmic approaches.
Tang, Elina   +2 more
core   +1 more source

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