Results 181 to 190 of about 50,655 (282)

EasyGeSe - a resource for benchmarking genomic prediction methods. [PDF]

BMC Genomics
Quesada-Traver C, Ariza-Suarez D, Studer B, Yates S.   +3 more
europepmc   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Optimizing genomic selection models for wheat breeding under contrasting water regimes in a mediterranean environment. [PDF]

Plant Methods
Yannam VRR, Lopes MS, Soriano JM.
europepmc   +1 more source

Characterization of Positive Reproducing Kernels. Applications to Green's Functions

American Journal of Mathematics, 1957
Aronszajn, N., Smith, K. T.
openaire   +3 more sources

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

New Properties of Holomorphic Sobolev-Hardy Spaces. [PDF]

Complex Anal Oper Theory
Gryc W, Lanzani L, Xiong J, Zhang Y.
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

BRMDA: prediction model for potential microbe-drug associations based on bilinear attention networks and random forest. [PDF]

Front Genet
Yu G, Chen F, Chen H, Tang S, Liang M, Liu X, Zeng B, Wang L.   +7 more
europepmc   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

ReaGP: integrating residual units and attention mechanisms in convolution neural network for genomic prediction. [PDF]

Genet Sel Evol
Li J, Guo P, Zhang Y, Ma H, Zhao Z, Wang Y, Wang Z, Chen Y, Xu L, Zhang L, Gao H, Gao X, Li J, Zhu B.   +13 more
europepmc   +1 more source