Results 91 to 100 of about 2,586,878 (296)
Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
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
Emerging experimental and computational methods for studying redox‐regulated structural transitions
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
A Profile Likelihood Theory for the Correlated Gamma-Frailty Model with Current Status Family Data
99學年度溫啟仲教師升等參考著作A profile likelihood inference is made for the regression coefficient and frailty parameters in the correlated gamma-frailty model for current status family data. With the introduction of an identifiability assumption, the identifiability
Chang, I-shou; Wen, Chi-chung; Wu, Yuh-jenn
core
Adjustements of the profile likelihood from a new perspective. [PDF]
Various modifications of the profile likelihood have been proposed over the past twenty years. Their main theoretical basis is higher-order approximation of some target likelihood, defined by a suitable model reduction via conditioning or marginalisation,
Salvan , Alessandra +2 more
core
Censored median regression and profile empirical likelihood
We implement profile empirical likelihood-based inference for censored median regression models. Inference for any specified subvector is carried out by profiling out the nuisance parameters from the plug-in empirical likelihood ratio function proposed
Subramanian, Sundarraman
core +1 more source
A novel two‐stage profile maximum likelihood estimator is proposed to estimate the source location and the systematic errors jointly, with the aim of addressing the problem of source localisation using angle‐only measurements from a single sensor with ...
Heng‐Yu Hu +2 more
doaj +1 more source
The Shewanella oneidensis Fic enzyme SoFic targets the switch‐I region of EF‐Tu for AMPylation
Fic enzymes mediate diverse post‐translational modifications across all domains of life, including AMPylation. Prokaryotic EF‐Tu can be AMPylated and deAMPylated by the conserved Fic enzyme SoFic. Structural and biochemical approaches were used to characterize the effect of AMPylation on EF‐Tu, SoFic's enzymatic activities, and the enzyme‐target ...
Svenja Runge +6 more
wiley +1 more source
To profile or to marginalize - A SMEFT case study
Global SMEFT analyses have become a key interpretation framework for LHC physics, quantifying how well a large set of kinematic measurements agrees with the Standard Model. This agreement is encoded in measured Wilson coefficients and their uncertainties.
Ilaria Brivio, Sebastian Bruggisser, Nina Elmer, Emma Geoffray, Michel Luchmann, Tilman Plehn
doaj +1 more source
Synechocystis strains deficient in succinate dehydrogenase (SDH) secrete more succinate than the WT under dark anaerobic conditions, supporting that SDH then primarily acts as SDH, not as a fumarate reductase. L‐aspartate oxidase (Laspo) from Synechocystis is functional under anaerobic conditions, reducing fumarate to succinate.
Kateryna Kukil +3 more
wiley +1 more source
Parameter Estimation in Semi-Linear Models Using a Maximal Invariant Likelihood Function [PDF]
In this paper, we consider the problem of estimation of semi-linear regression models. Using invariance arguments, Bhowmik and King (2001) have derived the probability density functions of the maximal invariant statistic for the nonlinear component of ...
Jahar L. Bhowmik, Maxwell L. King
core

