Results 101 to 110 of about 466,927 (310)

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

One for all and all for one: regression checks with many regressors [PDF]

We develop a novel approach to build checks of parametric regression models when many regressors are present, based on a class of sufficiently rich semiparametric alternatives, namely single-index models.
Patilea, Valentin, Lavergne, Pascal
core   +1 more source

Hyperosmotic stress‐induced redistribution of pre‐mRNA cleavage factor I subunits is associated with shifts in alternative polyadenylation

FEBS Open Bio, EarlyView.
Hyperosmotic stress triggers the relocation of the CFIm complex from the nucleus to the cytoplasm. This shift creates a nuclear ‘stoichiometric bottleneck’, limiting CFIm availability for mRNA processing. Consequently, specific mRNAs like NUDT21 and DICER1 undergo targeted 3′UTR shortening, demonstrating how spatial protein dynamics drive rapid ...
Hitomi Soumiya, Masatake Osawa, Hidefumi Fukumitsu   +2 more
wiley   +1 more source

Goodness-of-Fit Tests in Nonparametric Regression [PDF]

AMS classifications: 62G08, 62G10, 62G20, 62G30; 60F17.Bootstrap;empirical process;goodness-of-fit;location-scale regression;model diagnostics;nonparametric regression;test for independence;weak ...
Einmahl, J.H.J., Keilegom, I. van
core   +1 more source

Alternative methods for forecasting GDP [PDF]

An empirical forecast accuracy comparison of the non-parametric method, known as multivariate Nearest Neighbor method, with parametric VAR modelling is conducted on the euro area GDP. Using both methods for nowcasting and forecasting the GDP, through the
Patrick Rakotomarolahy, Dominique Guegan
core   +3 more sources

Regression Modeling for Spherical Data via Non-parametric and Least Square Methods

پژوهش‌های ریاضی, 2019
Introduction Statistical analysis of the data on the Earth's surface was a favorite subject among many researchers. Such data can be related to animal's migration from a region to another position.
mosa golalizadeh, m moghimbeigy
doaj  

Age at death during the Covid-19 lockdown in French metropolitan regions: a non parametric quantile regression approach

BMC Public Health
Background Lockdowns have been implemented to limit the number of hospitalisations and deaths during the first wave of 2019 coronavirus disease. These measures may have affected differently death characteristics, such age and sex.
Jonathan Roux, Marlène Faisant, Diane François, Olivier Retel, Alain Le Tertre   +4 more
doaj   +1 more source

Estimating individual tree growth with the k-nearest neighbour and k-Most Similar Neighbour methods

Silva Fennica, 2001
The purpose of this study was to examine the use of non-parametric methods in estimating tree level growth models. In non-parametric methods the growth of a tree is predicted as a weighted average of the values of neighbouring observations.
Sironen, Susanna, Kangas, Annika, Maltamo, Matti, Kangas, Jyrki   +3 more
doaj   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

DATA-DRIVEN RATE-OPTIMAL SPECIFICATION TESTING IN REGRESSION MODELS [PDF]

We propose new data-driven smooth tests for a parametric regression function. The smoothing parameter is selected through a new criterion that favors a large smoothing parameter under the null hypothesis.
Emmanuel Guerre, Pascal Lavergne
core