Ming D. Li, PhD
Human Genetics and Genomics, Genetics Epidemiology and Bioinformatics, Molecular Neuroscience of Drug Addiction
The primary research interest in Dr. Li's laboratory is to understand how tobacco smokers become addicted and why they cannot quit their smoking habit although they realize that tobacco smoking is harmful to their health.Mounting evidence suggests that certain aspects of smoking are influenced by genetic factors. However, the genetic factors responsible for tobacco dependence are largely unknown. One of the NIH-funded research projects in Dr. Li's laboratory is to identify susceptibility loci and genes for nicotine dependence using genome-wide linkage and association analysis approaches. Since 1999, more then 2,000 subjects representing approximately 600 smoker families of different ethnical populations have been recruited in multiple states of the U.S. and are being used for genetic analysis. Currently, we are concentrating on identification and characterization of hundreds of candidate genes selected from the positive regions identified by linkage analyses.
Another NIH-funded project in Dr. Li's laboratory is employing microchip and proteomic technologies to identify novel genes and biochemical pathways associated with nicotine dependence and nicotine withdrawal in experimental animals. Several versions of custom-designed microchips have been developed in the laboratory and are being used in a number of microarray projects. Dr. Li's laboratory is also using conventional molecular techniques such as Northern, RNase protection, real-time RT-PCR, in situ hybridization, Western, radioimmunoassay, radioligand binding assay, and immunohistochemistry in these projects and to investigate why nicotine suppresses appetite and increases energy expenditure of smokers.
Additionally, Dr. Li's laboratory is interested in Bioinformatics. To accomplish the goals of genetic mapping, cDNA microchip and other ongoing projects, a Bioinformatics research group has been formed in the laboratory. The scientists of this group work closely with the batch scientists in the laboratory and other institutions. The primary research areas of interest in our Bioinformatics effort include linkage and association analyses, microarray data mining and analysis, protein modeling and molecular evolutionary analysis.
The research in this laboratory is currently being carried out by a dozen of research staff at various levels including Research faculty, Scientists, Post-Doctoral Fellows, Research Associates and Research Assistants, with very different scientific disciplines such as Psychology, Pharmacology, Neurosciences, Molecular Biology, Genetics, Computer Sciences, Bioinformatics, or Biostatistics.