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Keynote - Drs. Mary Qu Yang and Jack Y. Yang
Date: July 14, 2008
Time: During the conference dinner (9:10 - 11:30 PM)
Location: Banquet Hall (Ballrooms 1-5)
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Dr. Mary Qu Yang
National Human Genome Research Institute National Institutes of Health (NIH) U.S. Dept. of Health of Human Services Bethesda, MD USA & Dr. Jack Y. Yang Harvard University Cambridge, Massachusetts USA |
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High performance computing has become a major focus of attention by government, industry, medical centers and academic institutions. The U.S. government has made this a “top national priority”, linking the development of a "data superhighway system" to national competitiveness and national research interest. High performance computing approaches have been used for sequence analysis, gene finding, protein structural prediction, all-atom simulation such as molecular dynamics and quantum calculations, modeling biological networks such as systems biology and more recently drug design and drug discovery. All these approaches are highly computationally demanding, in terms of compute load, communication speed, and memory load. Supercomputing based drug design and drug discovery use high-performance super-computers and bioinformatics approaches to discover, enhance, and study drugs and related biologically active molecules as well as the sites of protein interactions. Methods include molecular modeling using biophysical approaches such as molecular dynamics, semi-empirical quantum mechanics methods, ab initio quantum chemistry methods, density functional theory, receptor - ligand interactions and protein docking and so on. The success of the high-throughput drug design and drug discovery now directly relies on the high-performance supercomputing capabilities. Many research and computational products that were used to be considered impossible now proved to be feasible and effective with the help of today's supercomputing techniques. In particular, the identification of diseases relating to protein structural changes challenges biomedicine as the result of the sophisticated protein interaction networks that demand effective drug design using supercomputing based on mathematical, computational and biophysical models and algorithms for solving the model equations, and the bioinformatics techniques to analyze and validate the results. Those will need our deeper studies of biophysical phenomena and interesting biophysical and algorithmic problems using supercomputing.
High throughput sequencing and molecular imaging technologies marked the beginning of a new era for modern translational medicine and personalized healthcare. The impact of having the human sequence and personalized digital images in hand has also created tremendous demands of developing powerful supercomputing and computational intelligence approaches to handle the massive personalized healthcare data which will obviously have a profound effect on how biomedical research will be conducted toward the improvement of human health in the future. Recently, the National Human Genome Research Institute and National Cancer Institute, both part of NIH, U.S. Department of Health and Human Services, have launched The Cancer Genome Atlas (TCGA) with an overarching goal of understanding the molecular basis of cancer to improve our ability to diagnose, treat and prevent cancer. The perspective of the TCGA project is that “cancer is not a single disease but a collection of diseases that arise from different combinations of genetic changes”. Based on the mission of TCGA, we have proposed a further parallel paradigm on cancer: it is not only the genetic changes (i.e. mutations of genes) but also changes of gene expressions and regulatory networks that are ultimately responsible for cancer development. Under this parallel paradigm, not only mutations of genes cause changes in gene regulatory networks; but also un-mutated genes with differential expressions and alternative splicing may also induce changes in the differential regulatory networks (that also cause cancer) when cells are subjected to unusual environments. We have published a number of papers and delivered a number of invited keynote lectures regarding feasibility of detecting microscopic diseases at the IEEE and other international conferences and workshops.
In this keynote lecture, we will introduce the development of genomic functional analysis software tools which are important to human genome and cancer genome research. We are interested in high-quality computational research work in relating sequence to function and its scientific impact. We use a broad array of techniques, which combine our expertise in biomedical approaches with sequence-based informatics approaches. Until now, these two approaches have largely been undertaken separately. However, the evidence is clear that the synergies between these approaches are very powerful. We are integrating these two approaches in the pursuit of solutions to translational medicine and personalized healthcare.
Our aim is to develop next generation computational solutions for structural and functional genomics - such as predicting gene function and protein structure from sequence, in silico screening of leading compounds and designing new drugs, and annotation of genes for human genome and cancer genomes through automated approaches. The efficient utilization of very large databases combined with large-scale genomic computing is a significant computer science and engineering as well as biomedical problem, we focus on the software development of new generation of computational intelligence for the personalized healthcare and translational medicine that will lead to new understanding of human diseases and future treatment.
Drs. Jack and Mary Yang received their Ph.D. and M.S. degrees and Dr. Mary Yang received an additional MSECE degree, all from the Purdue University, West Lafayette main campus. They received their B.S. / Engr.D. degrees in China. Dr. Mary Qu Yang received her National Certificate of Post Doctoral Training from National Institutes of Health and U.S. Department of Health and Human Services. Dr. Jack Y. Yang received his Post Doctoral Research Training from Harvard Medical School, Harvard University, and Indiana University School of Medicine. Dr. Mary Qu Yang had been a professional engineer in software engineering and research scientist in electrical and biomedical engineering and Dr. Jack Y. Yang had been an assistant professor of Purdue Engineering School and IU Medical School of Indiana University Purdue University Indianapolis and Nanjing University. Dr. Mary Qu Yang was a recipient of the Outstanding Interdisciplinary Bilsland Dissertation Fellow for biological physics and computer engineering dual degrees at Purdue University, West Lafayette Main Campus, the NIH Fellow for National Human Genome Research and NIH-Oak Ridge, DOE research specialist fellowship. Drs. Jack and Mary received a number of distinguished awards including Best Paper Awards of Smart Engineering System Design Award for Distinguishing Benign and Malignant Tumors, Theoretical Developments in Computational Intelligence Award for Developing New Variants of Self-Organizing Feature Map Algorithms, Smart Engineering System Design Award for Classifying Multiply Labeled Proteins and IEEE Bioinformatics and Bioengineering Outstanding Achievement Awards. Drs. Jack and Mary Yang were Invited Keynote Plenary Speakers of a number of IEEE and other international conferences and workshops. Drs. Jack and Mary Yang have served as editors of more than a dozen international journals and conferences. Drs. Jack and Mary Yang were both trained as combined experimental and computational scientists with more than 15 years of teaching, research and engineering practice experience in software engineering and biomedicine. They have published more than 100 peer reviewed papers and book chapters and hold U.S. patents. Dr. Mary Qu Yang is the Editor-in-Chief of International Journal of Computational Biology and Drug Design and Dr. Jack Y. Yang is the Editor-in-Chief of International Journal of Functional Informatics and Personalized Medicine.
