Results 251 to 260 of about 179,787 (326)

Multi-trait/environment sparse genomic prediction using the SFSI R-package. [PDF]

Plant Genome
Lopez-Cruz M, de Los Campos G.
europepmc   +1 more source

Deep learning accelerated the discovery of multi‐principal element alloys with various strength‐toughness trade‐offs

Materials Genome Engineering Advances, EarlyView.
Coupling deep generative models with Pareto optimization, we uncover eight multiprincipal element alloys that outperform existing strength–toughness records after only three design–test cycles, showcasing a rapid data‐efficient route to balanced‐property alloy discovery across high‐dimensional composition spaces.
Chunhui Fan, Hong Luo, Qiancheng Zhao, Xuefei Wang, Hongxu Cheng, Yue Chang   +5 more
wiley   +1 more source

Genomic selection of maize test-cross hybrids leveraged by marker sampling. [PDF]

Plant Genome
Bernardeli A, Guilhen JHS, Oliveira ICM, Guimarães LJM, Borém A, Jarquin D, Pastina MM.   +6 more
europepmc   +1 more source

Space‐Time Smoothness and Parsimony in Covariance Functions

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT This paper challenges the trade off between computational efficiency and statistical accuracy within the framework of Gaussian space‐time processes. Under such a framework, the space‐time dependence is completely specified through the space‐time covariance function.
Tarik Faouzi, Emilio Porcu, Moreno Bevilacqua   +2 more
wiley   +1 more source

Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions. [PDF]

Plant Genome
Ali B, Mary-Huard T, Charcosset A, Moreau L, Rincent R.   +4 more
europepmc   +1 more source

Methods of causal effect estimation for high‐dimensional treatments: A radiotherapy simulation study

Medical Physics, EarlyView.
Abstract Background Radiotherapy, the use of high‐energy radiation to treat cancer, presents a challenge in determining treatment outcome relationships due to its complex nature. These challenges include its continuous, spatial, high‐dimensional, multi‐collinear treatment, and personalized nature, which introduces confounding bias.
Alexander Jenkins, Eliana Vasquez Osorio, Andrew Green, Marcel van Herk, Matthew Sperrin, Alan McWilliam   +5 more
wiley   +1 more source

Robust multi‐coil MRI reconstruction via self‐supervised denoising

Magnetic Resonance in Medicine, EarlyView.
Abstract Purpose To examine the effect of incorporating self‐supervised denoising as a pre‐processing step for training deep learning (DL) based reconstruction methods on data corrupted by Gaussian noise. K‐space data employed for training are typically multi‐coil and inherently noisy.
Asad Aali, Marius Arvinte, Sidharth Kumar, Yamin I. Arefeen, Jonathan I. Tamir   +4 more
wiley   +1 more source

Weighted GBLUP in Simulated Beef Cattle Populations: Impact of Reference Population, Marker Density, and Heritability. [PDF]

Animals (Basel)
Zhou L, Zhu L, Chang C, Ma F, Liu Z, Gu M, Na R, Zhang W.   +7 more
europepmc   +1 more source

Multi‐Frequency Electrical Impedance Myography as a Predictor of Muscle Function in Older Adults

Muscle &Nerve, EarlyView.
ABSTRACT Introduction/Aims This study examined the potential of multi‐frequency electrical impedance myography (EIM) to predict hand grip strength (HGS) variability among adults, including a large proportion of older adults, with and without sarcopenia.
Niladri Kumar Mahato, Buket Sonbas Cobb, Seward B. Rutkove, W. David Arnold, Brian C. Clark   +4 more
wiley   +1 more source

Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.). [PDF]

Plant Genome
Peng J, Lei X, Liu T, Xiong Y, Wu J, Xiong Y, You M, Zhao J, Zhang J, Ma X.   +9 more
europepmc   +1 more source