Research

研究方向

Research Areas

Zhang BioAI Lab 关注 AI 方法在药物安全性、环境健康风险和疾病机制研究中的应用。

Zhang BioAI Lab studies AI applications in drug safety, environmental health risk assessment, and disease mechanism discovery.

🧪 计算毒理学与风险预测

🧪 Computational Toxicology and Risk Prediction

构建药物和环境化合物的多终点毒性预测模型，覆盖肝毒性、基因毒性、细胞毒性、神经毒性和内分泌干扰等任务。

Developing multi-endpoint toxicity prediction models for drugs and environmental chemicals, including hepatotoxicity, genotoxicity, cytotoxicity, neurotoxicity, and endocrine disruption.

💊 药物相互作用与联合风险

💊 Drug Interaction and Joint Risk

发展基于图表示学习、预训练模型和临床数据挖掘的药物组合风险预测方法，用于识别潜在高风险药物组合。

Developing drug combination risk prediction methods based on graph representation learning, pretrained models, and clinical data mining.

🧬 功能性磷酸化与疾病机制

🧬 Functional Phosphorylation and Disease Mechanisms

结合蛋白结构、进化保守性、磷蛋白组数据和激酶机制分析，挖掘疾病相关功能性磷酸化位点。

Integrating protein structure, evolutionary conservation, phosphoproteomics, and kinase mechanism analysis to identify disease-related functional phosphorylation sites.

🤖 生物医学预训练与 BioAI

🤖 Biomedical Pretraining and BioAI

基于生物医学异质网络、分子结构和语义语料，构建可迁移、可解释的预训练表示学习模型。

Building transferable and interpretable pretrained representation learning models using biomedical heterogeneous networks, molecular structures, and semantic corpora.