Results 101 to 110 of about 16,222,653 (310)

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

FEBS 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, Ayaka Nagasato‐Ichikawa, Keita Iida, Shuhei Kimura, Akira Imamoto, Mariko Okada   +5 more
wiley   +1 more source

Non-parametric correlation structures and their respective embeddings in predictive analysis

Discover Applied Sciences
In data analysis, there is a natural connection between correlation and visual analysis. Correlation analysis enables the identification of relationships between attribute pairs in multidimensional datasets, while visual data analysis focuses on ...
Adam Dudáš
doaj   +1 more source

icenReg: Regression Models for Interval Censored Data in R

Journal of Statistical Software, 2017
The non-parametric maximum likelihood estimator and semi-parametric regression models are fundamental estimators for interval censored data, along with standard fullyparametric regression models.
Clifford Anderson-Bergman
doaj   +1 more source

ESTIMATING NON-PARAMETRIC AND PARAMETRIC TRANSFORMATION FUNCTIONS FROM SURVEY DATA: AN APPLICATION OF MINIMUM CROSS-ENTROPY [PDF]

A model of a (convex) technology of representative and non-representative firms in a heterogeneous sector is presented in non-parametric and parametric versions. The heterogeneity is specified with error terms.
Hoveid, Oyvind
core  

Emerging experimental and computational methods for studying redox‐regulated structural transitions

FEBS Letters, EarlyView.
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, Dana Reichmann, Gábor Erdős   +2 more
wiley   +1 more source

Hybrid Learning Model for intrusion detection system: A combination of parametric and non-parametric classifiers

Alexandria Engineering Journal
The growing digital transformation has increased the need for effective intrusion detection systems. Traditional intrusion detection systems face challenges in accurately classifying complex patterns.
C. Rajathi, P. Rukmani
doaj   +1 more source

GDP nowcasting with ragged-edge data : A semi-parametric modelling [PDF]

This papier formalizes the process of forecasting unbalanced monthly data sets in order to obtain robust nowcasts and forecasts of quarterly GDP growth rate through a semi-parametric modelling.
Patrick Rakotomarolahy, Dominique Guegan, Laurent Ferrara   +2 more
core  

Synergistic perspectives—How single‐molecule biophysics complement biochemical understanding

FEBS Letters, EarlyView.
In this review, we discuss how ensemble biochemistry and single‐molecule approaches are complementary, outline commonly used single‐molecule techniques, and illustrate their relevance through two representative case studies: chromatin organization by SMC complexes and pathway choice during DNA double‐strand break repair.
Sara De Bragança, Eline L. Jansen, Jorine M. Eeftens   +2 more
wiley   +1 more source

Parametric Interpretation of Non-Parametric Regression Models [PDF]

, 2014
The advantage of the parametric regression models is the possibility of interpretation of the parameters of the regression model, i.e. to determine the direction and strength of the influence of predictors on the dependent variable.
Stelmach, Jacek
core  

M[pi]log, Macromodeling via parametric identification of logic gates [PDF]

, 2003
This paper addresses the development of computational models of digital integrated circuit input and output buffers via the identification of nonlinear parametric models. The obtained models run in standard circuit simulation environments, offer improved
Stievano, Igor Simone, Maio, Ivano Adolfo, Canavero, Flavio   +2 more
core   +1 more source