views: 650
Information
Unknow
Sign in to view more
Experience
Sign in to view more
Education
Sign in to view more
Bio
Developing a drug costs in the order of a billion USD and takes some 10 years. Drug repositioning tries to reduce cost and time by applying drugs that are already on the market to new uses. With the avalanche of publicly available data on compounds, genes, proteins, and diseases and their relationships, there is a tremendous need for computational approaches to organize and analyze this data and finally predict novel uses. In our group we are specifically focusing on developing algorithms and analysis pipelines using networks, protein structures, text-mining and ontologies for this purpose. We currently focus on pancreas cancer as application, where we have a wealth of experimental data from collaborations with the medical faculty.
To identify novel HSP27 inhibitors, we developed screening algorithms, which identify remotely similar binding sites across evolutionary unrelated target proteins. We screen the entire known structural proteome and predicted and experimentally validated novel HSP27 inhibitors. We are currently testing the compounds in vivo.
Generally, the avalanche of publicly available data on compounds, genes, proteins, and diseases and their relationships creates a tremendous need for computational approaches to organize and analyze this data. In my group we are specifically focusing on developing algorithms and analysis pipelines using protein structures and sequencing data. We currently focus on cancer as application, where we have a wealth of experimental data from collaborations with medical groups.
To identify novel HSP27 inhibitors, we developed screening algorithms, which identify remotely similar binding sites across evolutionary unrelated target proteins. We screen the entire known structural proteome and predicted and experimentally validated novel HSP27 inhibitors. We are currently testing the compounds in vivo.
Generally, the avalanche of publicly available data on compounds, genes, proteins, and diseases and their relationships creates a tremendous need for computational approaches to organize and analyze this data. In my group we are specifically focusing on developing algorithms and analysis pipelines using protein structures and sequencing data. We currently focus on cancer as application, where we have a wealth of experimental data from collaborations with medical groups.
Research Interests
Papers
Sort
By YearBy Citation
Add Paper

View All
Ego Network
D-Core
Co-Author
Author Statistics
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