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Keynote Lecture - Dr. Mary Yang

Last modified 2015-07-12 21:32

Systems genomics approaches for streamlined big-data integrative genomics analysis
Dr. Mary Yang
Director of MidSouth Bioinformatics Center
Director of the Joint Bioinformatics Ph.D. Program of University of Arkansas
Little Rock Donaghey College of Engineering & Information Technology & University of Arkansas
Arkansas, USA

Date & Time: July 29 (Wednesday), 2015; 05:00pm - 05:40pm
Loction: Silver Room


    Rapid development of next-generation sequencing (NGS) technologies offers unprecedented opportunities to elucidate molecular mechanisms underlying diverse phenotypes utilizing the big-data from NGS. Our research shows that pathway-based biomarkers and drug targets can be identified by synergistically integrating different types of genomic data using systems biology techniques. Integrating multilayer genomic data requires us to develop streamlined computational approaches to gain biological insights from the big-data.

    While systems biology studies complex molecular interactions, genomics and systems biology can be combined into the integrative study of genomic landscapes and biological functions at cellular or organism level. The upcoming field can be referred to as systems genomics. However currently, for next-generation sequencing big-data analysis, there is no integrated package that can combine raw data processing, quality control, and downstream statistical and functional genomics analysis at systems biology level. In this invited keynote lecture, I will introduce streamlined methods that can process raw data, perform quality control, and analyze genomic big-data from whole genome sequencing, RNA-Seq, and ChIP-Seq. In addition, long non-coding RNAs (lncRNAs) have been shown to play important roles in various biological processes and have been implicated in disease. Although their regulatory mechanisms remain to be elucidated, high-throughput RNA sequencing analysis has provided us new abilities to annotate lncRNA transcripts, which can potentially advance our understanding of their biological functions. Since lncRNAs can regulate disease-associated genes, I will present our methods to integrate data from different platforms for an integrative downstream analysis using systems biology approaches, and introduce strategies of computation-intensive big-data analysis to facilitate biomedical discoveries including the regulatory and functional roles of lncRNAs. This lecture will illustrate systems biology based approaches to incorporate genomic multi-layer big-data to maximize the utility of the data and the advantages of integrative analysis for deeper understanding of underlying molecular mechanisms. Integrating multilayer big-data at the systems level can enable NGS to realize its full potential for personalized and precision medicine research. In this lecture, I will illustrate systems genomics approaches for the big-data integrative genomics analysis.


    Dr. Mary Yang is the Director of MidSouth Bioinformatics Center and Director of the Joint Bioinformatics Ph.D. Program of University of Arkansas Little Rock Donaghey College of Engineering & Information Technology and University of Arkansas for Medical Sciences. She received the MS, MSECE and Ph.D. degrees, all from Purdue University. She then completed a postdoctoral research training fellowship from the National Human Genome Research Institute in 2006, and continuously worked on various large-scale research projects at NIH. During her 7-year tenure at NIH, she contributed to various genomics and systems biology research projects. She was recruited by the University of Arkansas in 2013 to lead the joint bioinformatics program. Dr. Yang has been Founding Editor-in-Chief of International Journal of Computational Biology and Drug Design, a NIH PubMed fully indexed journal and is on editorial broads of Journal of Supercomputing and International Journal of Pattern Recognition and Artificial Intelligence. She served as a Steering Committee Member of NIH funded AR INBRE and bioinformatics core director for the NIH funded research network for Arkansas and MidSouth. She has been the recipient of NIH Fellows Award for Research Excellence, NIH Academic Research Enhancement Award, Bilsland Dissertation Fellowship, Purdue Research Foundation Fellowship, IEEE and ISIBM Bioinformatics and Bioengineering Outstanding Achievement Awards, and Basic Scientific Research Award of Arkansas Science and Technology Authority. Dr. Yang’s research laboratory is supported by NIH and ASTA. She has published over 100 research articles in both computer science and biomedical sciences.
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