Research on Network Construction and Application of Novel Drug Repositioning Strategies Background During the COVID-19 pandemic, researchers and pharmaceutical companies have been dedicated to developing treatments and vaccines. Drug repositioning, due to its shortcut, is considered a rapid and effective response strategy. Drug repositioning attemp...
Research Report on Potential Biomarkers for Early Detection of ADHD: Phase-Based Functional Brain Connectivity and Graph Theory Analysis This is a research report titled “Potential Biomarkers for Early Detection of ADHD: Using Phase-Based Functional Brain Connectivity and Graph Theory Analysis”. This study was conducted by Farhad Abedinzadeh Torgha...
Brain Science Research Inspires AI Algorithms: Neural Mechanisms of Knowledge Assembly Background Introduction When new information enters the brain, human pre-existing knowledge of the world can quickly change through a process called “knowledge assembly.” Recently, in a study conducted by Nelli et al., the neural correlates of knowledge assembly ...
Graph Theory Analysis of Brain Network Topology Structure in Patients with Primary Angle-Closure Glaucoma Research Background Glaucoma is a global blinding eye disease characterized by optic nerve damage and elevated intraocular pressure (IOP) (Kang and Tanna 2021). Among various types of glaucoma, Primary Angle-Closure Glaucoma (PACG) is particula...
Research Report on Changes in Functional Connectivity in Post-Stroke Epilepsy (PSE) Patients Based on Source-Level EEG and Graph Theory Research Background Epilepsy has various etiologies, including idiopathic, congenital, head trauma, central nervous system infections, brain tumors, neurodegenerative diseases, and cerebrovascular diseases. Among t...
Research on Drug-Disease Association Prediction Using Graph Contrastive Learning Based on Layered Negative Sampling The prediction of drug-disease associations (RDAs) plays a critical role in unveiling disease treatment strategies and promoting drug repurposing. However, existing methods mainly rely on limited domain-specific knowledge when predict...
Research Report on Immunotherapy Efficacy Prediction for Non-Small Cell Lung Cancer: A Study of Multi-View Adaptive Weighted Graph Convolutional Networks Background Introduction Lung cancer is a highly prevalent and poorly prognostic malignant tumor with a persistently high mortality rate. Among all lung cancer patients, Non-Small Cell Lung Cancer ...
Background and Research Motivation It is well-known that food nutrition is closely related to human health. Scientific research has shown that improper dietary nutrition is linked to more than 200 diseases. Especially when considering the metabolic processes of gut microbiota, the complex interactions between food nutrients and diseases become diff...
Predicting Drug-Target Affinity Based on Learning Protein Knowledge from Biological Networks Background The prediction of drug-target affinity (DTA) plays a crucial role in drug discovery. Efficient and accurate DTA prediction can significantly reduce the time and economic costs of new drug development. In recent years, the explosive development of...
Application of Knowledge-Enhanced Graph Topic Transformer in Interpretable Biomedical Text Summarization Research Background Due to the continuous increase in the volume of biomedical literature, the task of automatic biomedical text summarization has become increasingly important. In 2021 alone, 1,767,637 articles were published in the PubMed data...