Results 91 to 100 of about 3,727,733 (308)

Discussion: Latent variable graphical model selection via convex optimization

, 2012
Discussion of "Latent variable graphical model selection via convex optimization" by Venkat Chandrasekaran, Pablo A. Parrilo and Alan S. Willsky [arXiv:1008.1290].Comment: Published in at http://dx.doi.org/10.1214/12-AOS984 the Annals of Statistics ...
Giraud, Christophe, Tsybakov, Alexandre
core   +1 more source

Variable selection using pseudo-variables

, 2018
Penalized regression has become a standard tool for model building across a wide range of application domains. Common practice is to tune the amount of penalization to tradeoff bias and variance or to optimize some other measure of performance of the estimated model.
Hu, Wenhao, Laber, Eric, Stefanski, Leonard   +2 more
openaire   +2 more sources

An Improved Forward Regression Variable Selection Algorithm for High-Dimensional Linear Regression Models [PDF]

, 2020
Yanxi Xie, Yuewen Li, Zhijie Xia, Ruixia Yan   +3 more
openalex   +1 more source

Reciprocal control of viral infection and phosphoinositide dynamics

FEBS Letters, EarlyView.
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley   +1 more source

Spatiotemporal and quantitative analyses of phosphoinositides – fluorescent probe—and mass spectrometry‐based approaches

FEBS Letters, EarlyView.
Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho, Shin Morioka, Junko Sasaki, Takehiko Sasaki   +3 more
wiley   +1 more source

Bayesian Model Averaging and Regularized Regression as Methods for Data-Driven Model Exploration, with Practical Considerations

Stats
Methodological experts suggest that psychological and educational researchers should employ appropriate methods for data-driven model exploration, such as Bayesian Model Averaging and regularized regression, instead of conventional hypothesis-driven ...
Hyemin Han
doaj   +1 more source

Variable Selection in Time Series Forecasting Using Random Forests

Algorithms, 2017
Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored.
Hristos Tyralis, Georgia Papacharalampous   +1 more
doaj   +1 more source

An intracellular transporter mitigates the CO2‐induced decline in iron content in Arabidopsis shoots

FEBS Letters, EarlyView.
This study identifies a gene encoding a transmembrane protein, MIC, which contributes to the reduction of shoot Fe content observed in plants under elevated CO2. MIC is a putative Fe transporter localized to the Golgi and endosomal compartments. Its post‐translational regulation in roots may represent a potential target for improving plant nutrition ...
Timothy Mozzanino, Meijie Li, Cécile Fizames, Mattia Adamo, Laurence Lejay, Christian Dubos, Matthieu Platre, Antoine Martin   +7 more
wiley   +1 more source

Comparison of four variable selection methods to determine the important variables in predicting the prognosis of traumatic brain injury patients by support vector machine

Journal of Research in Medical Sciences, 2019
Background: Large amounts of information have called for increased computational complexity. Data dimension reduction is therefore critical to preliminary analysis.
Saeedeh Pourahmad, Soheila Rasouli-Emadi, Fatemeh Moayyedi, Hosseinali Khalili   +3 more
doaj   +1 more source

A Cre‐dependent lentiviral vector for neuron subtype‐specific expression of large proteins

FEBS Letters, EarlyView.
We designed a versatile and modular lentivector comprising a Cre‐dependent switch and self‐cleaving 2A peptide and tested it for co‐expression of GFP and a 2.8 kb gene of interest (GOI) in mouse cortical parvalbumin (PV+) interneurons and midbrain dopamine (TH+) neurons.
Weixuan Xue, Sandrine Picaud, Régine Hepp, Stéphanie Pons, Uwe Maskos, Bertrand Lambolez, Ludovic Tricoire   +6 more
wiley   +1 more source