PLXFPred: interpretable cross-attention networks with hierarchical fusion of multi-modal features for predicting protein–ligand interactions and affinities

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Journal
Bioinformatics
Published
2026-01-01
DOI
https://doi.org/10.1093/bioinformatics/btaf662
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

PLXFPred: interpretable cross-attention networks with hierarchical fusion of multi-modal features for predicting protein–ligand interactions and affinities

Ye Sun, Yonghong Hu, Wenge Yang, Ruilin Cai et al.
Bioinformatics
Computational Drug Discovery Methods
article

PLXFPred: interpretable cross-attention networks with hierarchical fusion of multi-modal features for predicting protein–ligand interactions and affinities

Ye Sun, Yonghong Hu, Wenge Yang, Ruilin Cai, Ziteng Wang
article en

Abstract

No abstract available for this paper.
BioinformaticsVol. 42(1)
Nanjing Tech University (CN), Nanjing University of Industry Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 91%
Computational Drug Discovery Methods
DOIOpen Access PDFOpenAlex
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PLXFPred: interpretable cross-attention networks with hierarchical fusion of multi-modal features for predicting protein–ligand interactions and affinities — Ye Sun, Yonghong Hu, et al. · Bioinformatics (2026) | TGRS Research Map | TGRS