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Titlebook: Applied Intelligence; First International De-Shuang Huang,Prashan Premaratne,Changan Yuan Conference proceedings 2024 The Editor(s) (if ap

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51#
發(fā)表于 2025-3-30 09:21:51 | 只看該作者
Enzyme Turnover Number Prediction Based on Protein 3D Structureso verify the effectiveness of the model, several enzyme reaction datasets were constructed, and multiple groups of comparative experiments were conducted. The experimental results demonstrate the feasibility of using 3D protein structures for enzyme function prediction, which opens up avenues for fu
52#
發(fā)表于 2025-3-30 13:48:33 | 只看該作者
53#
發(fā)表于 2025-3-30 17:11:34 | 只看該作者
Imputation of Compound Property Assay Data Using a Gene Expression Programming-Based Methodromosome population. Experimental results on three compound property assay related datasets demonstrates that the proposed method generally outperforms the state-of-the-art methods in imputing missing data of compound property assays.
54#
發(fā)表于 2025-3-30 20:49:43 | 只看該作者
Conference proceedings 2024ICAI 2023, held in Nanning, China, December 8–12, 2023..The 64 full papers presented in this proceedings were carefully selected and reviewed from 228 submissions. The papers cover a wide range on theoretical aspects of biomedical data modeling and mining; computer vision; and deep learning. They we
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發(fā)表于 2025-3-31 03:36:26 | 只看該作者
56#
發(fā)表于 2025-3-31 08:17:17 | 只看該作者
Paula Ungureanu,Diego Maria Macriormation contained within the prototype sets during the iterative process, we generate a prior mask from this information and provide coarse spatial location about the target for the model through a simple prior-guided attention module (PGA). Experiments on three different datasets validate that our proposed approach outperforms existing methods.
57#
發(fā)表于 2025-3-31 09:31:00 | 只看該作者
58#
發(fā)表于 2025-3-31 14:33:05 | 只看該作者
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