生物医学大数据-凯时尊龙

主要研究大容量、多类型、高维度、高不确定性生物医学大数据的标准化管理、高效并行计算、重大疾病基因组学及影像组学关联关系分析、疾病生物标志物快速筛选和靶向药物研发、基于大规模人群队列的重大疾病风险评估及预警模型等，为疾病诊断、治疗和预防提供准确、全面、全新的认识。以临床实际需求为导向，通过整合计算生物学与临床数据，用智能计算技术更准确的预测个体患病风险和预后，实现疾病的精准化治疗。

he mainly studies the standardized management of large-capacity, multi-type, high-dimensional, high-confident biomedical big data, efficient parallel computing, analysis of major disease genomics and imaging ensemble association, rapid screening of disease biomarkers, and targeted drug development. based on the large-scale population cohort of major disease risk assessment and early warning models, he provides an accurate, comprehensive and new understanding of disease diagnosis, treatment and prevention. guided by clinical actual needs, through the integration of computational biology and clinical data, intelligent computing technology can more accurately predict individual risk and prognosis, and achieve precise treatment of diseases.