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Titlebook: Bioinformatics Research and Applications; 20th International S Wei Peng,Zhipeng Cai,Pavel Skums Conference proceedings 2024 The Editor(s) (

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樓主: Bunion
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發(fā)表于 2025-3-25 07:13:18 | 只看該作者
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發(fā)表于 2025-3-25 18:16:50 | 只看該作者
,Spatial Gene Expression Prediction from?Histology Images with?STco,n. We utilized spatial transcriptomics data from two different tumors generated by the 10 times Genomics platform: human HER2 positive breast cancer (HER2+) and human cutaneous squamous cell carcinoma (cSCC) datasets. The experimental results demonstrate the superiority of STco compared to other met
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發(fā)表于 2025-3-26 02:53:30 | 只看該作者
,Dendritic SE-ResNet Learning for?Bioinformatic Classification,those models, our model attains a classification accuracy of 91.6%, marking an advancement of 2.7% over SE-ResNet. Additionally, our model demonstrates an F1-score of 92.4%, exhibiting an improvement of 4.4% compared to SE-ResNet.
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發(fā)表于 2025-3-26 07:16:18 | 只看該作者
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發(fā)表于 2025-3-26 09:20:19 | 只看該作者
,CircMAN: Multi-channel Attention Networks Based on?Feature Fusion for?CircRNA-Binding Protein Site ing bidirectional gated recurrent units and self-attention. The CircMAN method achieved an AUC of 0.923 on 37 circRNA datasets. Its effectiveness was confirmed through comparisons with five different methods and multiple ablation experiments. The source code can be available at ..
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發(fā)表于 2025-3-26 15:50:56 | 只看該作者
,A Novel Combined Embedding Model Based on?Heterogeneous Network for?Inferring Microbe-Metabolite Intabolite interactions. First, we build a heterogeneous network, which consists of microbe-metabolite pairs, microbial internal interaction network, and metabolite internal interaction network. Then, we utilize paired embeddings obtained from an autoencoder to extract fine-grained pairwise informatio
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發(fā)表于 2025-3-26 17:57:57 | 只看該作者
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