Drug-drug interactions (DDI) may lead to unexpected side effects, which is a growing concern in both academia and industry. Many DDIs have been reported, but the underlying mechanisms are not well understood. Predicting and understanding DDIs can help researchers to improve drug safety and protec...
Decoding is to reconstruct the network to predict unknown drug-drug interaction. The experimental results show that our model has advanced performance and is superior to other existing advanced methods. Case study also shows that MSResG has practical significance....
Leskovec说:“今天,药物的副作用基本上都是偶然发现的。但我们方法可以提供更加有效和安全的治疗方法。” 翻译:夏佳豪原文地址:https://news.stanford.edu/2018/07/10/ai-predicts-drug-pair-side-effects/?from=singlemessage论文地址:https://academic.oup.com/bioinformatics/article/34/13/i457/5045770 推荐阅读...
BMC Bioinformatics 2022, 23(Suppl 4):129 https://doi.org/10.1186/s12859-022-04664-4 BMC Bioinformatics RESEARCH Open Access DualGCN: a dual graph convolutional network model to predict cancer drug response Tianxing Ma1, Qiao Liu2, Haochen Li3, Mu Zhou4, Rui Jiang1 and ...
DDI-GCN: Drug-drug interaction prediction via explainable graph convolutional networks 2023, Artificial Intelligence in Medicine Citation Excerpt : First, the model architecture can be explored and improved. As regular GCNs may suffer from complexity and redundant node information in the process of propa...
Whole genome sequencing of multiple Leishmania donovani clinical isolates provides insights into population structure and mechanisms of drug resistance Visceral leishmaniasis is a potentially fatal disease endemic to large parts of Asia and Africa, primarily caused by the protozoan parasite Leishmania dono....
翻译:夏佳豪 编辑:孟婕 原文地址: https://news.stanford.edu/2018/07/10/ai-predicts-drug-pair-side-effects/?from=singlemessage 论文地址: https://academic.oup.com/bioinformatics/article/34/13/i457/5045770
https://news.stanford.edu/2018/07/10/ai-predicts-drug-pair-side-effects/?from=singlemessage 论文地址: https://academic.oup.com/bioinformatics/article/34/13/i457/5045770 推荐课程 打开网易新闻 查看精彩图片 推荐阅读 图网络——悄然兴起的深度学习新浪潮 ...
GCN的核心思想是通过聚合邻居节点的信息来更新每个节点的表示。在GCN中,边要素(Edge Features)是指连接节点的边的属性或特征,这些特征可以为图卷积操作提供额外的信息,从而增强模型的表达能力。 基础概念 边要素:在图结构中,边通常不仅仅是一个连接两个节点的无特征链接。边要素可以是任何与边相关的属性,例如社交...
Researchers utilized an attention-based GCN to extract drug-drug interaction relationships [28]. In particular, Zw et al. [48] proposed a propagation graph neural network with an attention mechanism to detect rumors on social media. The attention mechanism helped to adjust the weight of each ...