报告题目: Network-based computational framework for integrating multi-dimensional data

报告人:邹秀芬教授 武汉大学

报告时间: 2024年5月23日16:30-18:00

报告地点:兴庆校区数学与统计学院2-2会议室

报告摘要:With the advance of high throughput sequencing, multi-dimensional data are generated. Detecting dependence/correlation between these datasets is becoming one of most important issues in multi-dimensional data integration and co-expression network construction. In this talk, we presented several new indexes for testing both linear and nonlinear correlation between two matrices. Further, these indexes were applied to infer gene-isoform co-expression networks by using exon-level RNA-Seq data and successfully predict the distinct biological functions of gene isoforms.

专家简介: 邹秀芬, 武汉大学数学与统计学院 二级教授，博士生导师，中国工业与应用数学学会数学生命科学专业委员会副主任。长期从事数学与生物医学等交叉学科研究。近年来主持承担了国家自然科学基金重点项目、面上项目和科技部国家重大研究计划课题等科研课题。在复杂疾病的海量数据集成、多尺度建模和复杂疾病的优化控制等方面取得了一系列成果，已在“PNAS”, “Information Sciences”, “PLOS Computational biology”, “IEEE Transactions on Biomedical Engineering”等国际重要学术期刊上发表相关的学术论文。