Drug repositioning offers promising prospects for accelerating drug discovery by identifying
potential drug–disease associations (DDAs) for existing drugs and diseases. Previous …

The identification of drug–target interaction (DTI) is crucial for drug discovery. However, how
to reduce the graph neural network's false positives due to its bias and negative transfer in …

Automated arrhythmia detection using electrocardiogram (ECG) signals is critical for
cardiovascular disease prevention and treatment. However, the widely used CNN-based …

Drug-disease association prediction is an important part of drug discovery, which can help
researchers uncover potential drug candidates and disease targets more accurately to deal …

Drug repurposing offers a viable strategy for discovering new drugs and therapeutic targets
through the analysis of drug–gene interactions. However, traditional experimental methods …

Drug combination therapies are well-established strategies for the treatment of cancer with
low toxicity and fewer adverse effects. Computational drug synergy prediction approaches …

Non-coding RNAs (ncRNAs), which do not encode proteins, have been implicated in
chemotherapy resistance in cancer treatment. Given the high costs and time requirements of …

The extraction of biomedical data has significant academic and practical value in
contemporary biomedical sciences. In recent years, drug repositioning, a cost-effective …

Substructures are crucial factors influencing material molecular properties, and the effective
identification of molecular substructures can accelerate novel material discovery. The …

This study introduces a dataset for drug-bacteria associations (DBA) that affects humans.
Our contribution extends beyond merely curating the association matrix; we also conduct …