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The Dark Side of STING in The Neuropathology of NiemannPick DiseaseType
Unconventional Conjugation in Silsesquioxanes
Characterization of computational power in measurement-based quantumcomputati...
生成式人工智能的技术演进与行业应用
报告题目:
Toward Personalized Medicine
 报告人:
Quick Que
Associate Investigator, Translational Genomics Research Institute 
and Co-founder, Sino Sonoran Pharmaceuticals
报告时间:
2007-10-10 14:30
报告地点:
FIT大楼,1区312
主办单位:
计算机科学与技术系
  简介:

Abstract

Personalized medicine in modern drug development is a sophisticated integration of translational biology research and basic bioinformatics. The impact of human genome sequencing on drug development has been tremendous. Many developers enjoyed the advantages of in silico molecular modeling, high-throughput screening, pharmacogenomics approaches, and access to databases containing genomic and proteomic information. In addition, massive amount of data have been generated from different layers of biology complexity, introducing new challenges on data integration and database development. Here, I will present some achievements of TGen drug discovery program, emphasizing on genome-wide RNAi screening, target validation, and their application in personalized medicine.

 

Biography:   

Dr. Que received his Ph.D. degree in Biochemistry and microbiology from Cornell University in 2002. His postdoc training was in Genomics Institute of the Norvartis Research Foundation (GNF), San Diego where he focused on developing new anticancer drugs by combining high-throughput small molecule screening with other genomic approaches. In 2004, he joined TGen as an associate investigator and established a world-class RNAi screening center. He had experience in pharmacogenomic research with pharmaceuticals and biotech companies in facilitating drug discovery and development. He also serves as SAB members in several biotech companies and institutes.

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