Deep learning model predicts rice protein interactions from sequence data
A new deep learning framework called RCNNricePPI predicts rice protein-protein interactions from amino acid sequences, achieving an accuracy of 0.8996 ...
A new deep learning framework called RCNNricePPI predicts rice protein-protein interactions from amino acid sequences, achieving an accuracy of 0.8996 ...
A 2026 review examines altered protein-protein interactions as breast-cancer therapeutic targets and diagnostic biomarkers, while identifying heterogeneity, drug resistance, single-cell ...
Genomics has a stubborn arithmetic problem. In most modern association studies, the number of candidate genes runs into the tens ...
A new study shows that alternative splicing, especially through microexons shorter than five amino acids, fine-tunes protein interaction interfaces to ...
Researchers have developed DyME, an open-source platform that automates high-throughput mutagenesis, molecular dynamics simulation, and comparative analysis of thousands of ...
A Melbourne-led proteomics study has shown for the first time that the protein interaction partners of the anticoagulant protein C ...
Researchers have devised a pooled AlphaFold3 screening strategy that cuts the number of computational jobs needed to map an entire ...
A large-scale evolutionary analysis shows that viral protein mimics and the host proteins they impersonate are deeply conserved, revealing that ...
A comprehensive review maps how protein-protein interactions between plant viruses and their hosts drive infection and defense, and shows how ...
Researchers have developed NMPPI, a lightweight deep learning framework that predicts protein-protein interactions using only sequence and network structure data ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine