基本信息
浏览量:6
职业迁徙
个人简介
Research Interests
The last century has witnessed the tremendous advancement of Biological Sciences. The availability of massive biological data, high-performance computers, efficient computational algorithms, and mathematical and physical models have paved the way for Biological Sciences to undertake a historic transition from being qualitative, phenomenological, and descriptive to being quantitative, analytical, and predictive. Under this transition, modern Mathematical Biology will be fundamentally changed from macroscale modelings (of species, population, disease, blood fluid, etc) to molecular based analysis (of protein, DNA, gene, virus, etc).
Dr. XIA's group focuses on Molecular Based Mathematical Biology (MBMB). The essential idea is to use computational tools from PDE, differential geometry, algebraic topology and statistical learning to study the biomolecular structure, flexibility, dynamics, and functions. His recent interests are topological data analysis (TDA), topology based machine learning/deep learning models, and their applications in drug design.
The last century has witnessed the tremendous advancement of Biological Sciences. The availability of massive biological data, high-performance computers, efficient computational algorithms, and mathematical and physical models have paved the way for Biological Sciences to undertake a historic transition from being qualitative, phenomenological, and descriptive to being quantitative, analytical, and predictive. Under this transition, modern Mathematical Biology will be fundamentally changed from macroscale modelings (of species, population, disease, blood fluid, etc) to molecular based analysis (of protein, DNA, gene, virus, etc).
Dr. XIA's group focuses on Molecular Based Mathematical Biology (MBMB). The essential idea is to use computational tools from PDE, differential geometry, algebraic topology and statistical learning to study the biomolecular structure, flexibility, dynamics, and functions. His recent interests are topological data analysis (TDA), topology based machine learning/deep learning models, and their applications in drug design.
研究兴趣
论文共 100 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
CoRR (2024): 1016-1025
COMPUTERS IN BIOLOGY AND MEDICINE (2024): 107918-107918
FOUNDATIONS OF DATA SCIENCEno. 0 (2024): 0-0
CoRR (2023)
引用0浏览0EI引用
0
0
arxiv(2023)
Methods in molecular biology (Clifton, N.J.) (2023): 307-318
引用0浏览0WOS引用
0
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn