In bioinformatics research, traditional machine-learning methods have demonstrated
efficacy in addressing Euclidean data. However, real-world data often encompass non …

The time-consuming and expensive nature of traditional drug discovery necessitates a cost-
effective approach to facilitate disease treatment. Drug repositioning, discovering innovative …

The integration of high-throughput genomic sequencing and advanced AI algorithms is
revolutionizing the fields of medicine and pharmaceuticals, particularly in the areas of …

Healthcare knowledge graphs (HKGs) are valuable tools for organizing biomedical concepts
and their relationships with interpretable structures. The recent advent of large language …

本文构建了一个新的预测化合物–蛋白质关联关系的端到端的模型, 可直接输入样本序列后直接
输出预测结果, 命名为“CT-CPI”. 在此方法中, 模型主要由嵌入模块, CNN 模块, transformer 模块 …

Numerous machine learning strategies have been utilized and evaluated to improve and
optimize predictions of drug-target interactions. The Support Vector Machines (SVM) …

Rocket engines occasionally experience abnormal phenomena such as excessive vibration
and high rotational speed during flight, and the mechanism behind these occurrences is …