Results 261 to 270 of about 2,429,355 (361)

Unveiling Salt Tolerance Mechanisms in Plants: Integrating the KANMB Machine Learning Model With Metabolomic and Transcriptomic Analysis

open access: yesAdvanced Science, EarlyView.
Salt stress endangers coastal cereal crops, requiring resilient crop solutions. This study employs machine learning (KANMB) to analyze multi‐omics data from halophyte Spartina alterniflora, revealing 226 salt‐stress biomarkers and linking them to tolerance pathways. The MYB gene SaMYB35 regulates flavonoid biosynthesis under salinity.
Shoukun Chen   +7 more
wiley   +1 more source

A Novel Dual‐Network Approach for Real‐Time Liveweight Estimation in Precision Livestock Management

open access: yesAdvanced Science, EarlyView.
A novel dual‐network framework is proposed for real‐time, non‐contact liveweight estimation of pigs. By extracting contour information instead of segmented images, the method achieves high accuracy (R2 = 0.993) and an exceptional speed of 1131.6 FPS. This approach enhances automation in livestock farming, providing a scalable and efficient solution for
Ximing Dong   +6 more
wiley   +1 more source

DiffMC‐Gen: A Dual Denoising Diffusion Model for Multi‐Conditional Molecular Generation

open access: yesAdvanced Science, EarlyView.
DiffMC‐Gen, a dual‐diffusion model for 2D and 3D molecular generation, simultaneously optimizes multiple key objectives across the drug design process, enabling the generation of novel, target‐specific small‐molecule ligands with high therapeutic potential.
Yuwei Yang   +7 more
wiley   +1 more source

A Phase‐Separated SR Protein Reprograms Host Pre‐mRNA Splicing to Enhance Disease Susceptibility

open access: yesAdvanced Science, EarlyView.
This study identifies SR30, a splicing factor, as a negative regulator of tomato immunity. During Phytophthora infestans infection, the elevated SR30 forms nuclear condensates to suppress the alternative splicing (AS) of defense‐related genes in a phase separation manner.
Dong Yan   +11 more
wiley   +1 more source

Explainable Deep Multilevel Attention Learning for Predicting Protein Carbonylation Sites

open access: yesAdvanced Science, EarlyView.
Selective carbonylation sites (SCANS) are conceptualized, designed, evaluated, and released. SCANS captures segment‐level, protein‐level, and residue embeddings features. It utilizes elaborate loss function to penalize cross‐predictions at the residue level.
Jian Zhang   +6 more
wiley   +1 more source

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