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报告摘要：Bioinformatics is driven by data in principle. Today, we are in the big data era, and the bio-technology develops very fast in the last two decades, from all kinds of traditional arrays to next-generation sequencing, and even to PACBIO single molecular sequencing technology. These data provide huge information for us to understand complex biological system at different levels. My two long term goals are (i) understanding of how functional machineries are encoded in a bacterial genome; and (ii) development of enabling computational techniques in support of the above scientific studies. In this talk, I will show my experiences in genomic and transcriptomic data mining and biological systems modeling in bacterial bioinformatics.

报告人简介：I am currently an assistant research scientist and a group leader in Biochemistry & Molecular biology department at the University of Georgia. And I am going to take a tenure-track assistant professor position at South Dakota State University later this summer. I was trained as a mathematician with a Ph.D. in operations research (focusing on graphical modeling and combinatorial optimization); and I have been working in a bioinformatics lab in the past six years, initially as a visiting student, then as a postdoc and now a research assistant scientist. Hence, I view myself as a well-trained bioinformatics researcher and computational modeler of biological data and systems. My technical strength is in developing combinatorial optimization techniques and data mining and modeling with the advent of high-throughput Omics technologies. Until now, I have published 25 papers on reputed bioinformatic journals; and have gained substantial experience in developing and applying advanced software techniques / web databases in carrying out my own bioinformatics research in both prokaryotic and eukaryotic areas. Through independent investigation and collaborative studies with numerous biologists, I have gained general knowledge and developed a strong and long-term interest in (1) characterization of bacterial genomic organization and (2) elucidation of metabolic networks and associated regulatory systems.