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IRGL-RRI: interpretable graph representation learning for plant RNA–RNA interaction discovery
Published 2025-06-01“…To address this, this study proposes an interpretable graph representation model for accurate plant RRI prediction. The model enriches sample information by extracting features of different bases from plant RNA data and reconstructs these features using an algorithmic hierarchy approach to capture more complex patterns. …”
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Decoding a Cognitive Performance State From Behavioral Data in the Presence of Auditory Stimuli
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Influence of scale effect on flow field offset for ships in confined waters
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Distinguishing benign and malignant myxoid soft tissue tumors: Performance of radiomics vs. radiologists.
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Investigating performance and variability of NIF ICF experiments with deep learning
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Using Ray Tracing to Improve Bridge Monitoring With High-Resolution SAR Satellite Imagery
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THE EFFECT OF SUPPORT PLATE ON DRILLING-INDUCED DELAMINATION
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Energy-Efficient Hydraulic System for Hexapod Robot Based on Two-Level Pressure System for Oil Supply
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Numerical simulation of inclined filament under biomagnetic fluid flow
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