AIMRC Seminar: A Guide for Algorithms and Tools for Multi-Omics Data Integration and Analysis

University Relations

Professor Xintao Wu

The Arkansas Integrative Metabolic Research Center will host professor Xintao Wu, the Charles D. Morgan/Acxiom Endowed Graduate Research Chair in Computer Science and Computer Engineering at 12:55 p.m. Wednesday April 26, in ENGR 209, when Wu will discuss the numerous algorithms and tools developed for data integration and analysis, and how to identify, choose and implement the appropriate solutions for a researcher's needs.

With the adoption of high-throughput techniques and the availability of multi-omics data generated from a large set of samples, numerous algorithms and tools have been developed for data integration and analysis. However, due to inherent differences among multi-omics data and the wide array of available algorithms and tools, the identification and choice of appropriate tools for a researcher's needs is challenging. In this talk, Wu will overview tools and computational methods that adopt integrative approaches to analyze multi-omics data. In particular, he will discuss methodology, applicability, and limitations. He also provide a brief introduction to multi-omics data repositories and popular visualization portals. The talk will conclude with a discussion of challenges and future research directions for multi-omics data integration and analysis.

Wu currently serves as the data science core director for the Arkansas Integrative Metabolic Research Center. He was a faculty member in the College of Computing and Informatics at the University of North Carolina at Charlotte from 2001 to 2014. He received his B.S. degree in Information Science from the University of Science and Technology of China in 1994, M.E. degree in Computer Engineering from the Chinese Academy of Space Technology in 1997, and a Ph.D. in Information Technology from George Mason University in 2001.

Wu's major research interests include data mining, privacy and security, fairness aware learning, and big data analysis He has published over 150 scholarly papers and served on editorial boards of several international journals and many program committees of top international conferences in data mining and AI. Wu is also a recipient of NSF CAREER Award (2006) and several paper awards including PAKDD'13 Best Application Paper Award, BIBM'13 Best Paper Award, CNS'19 Best Paper Award, and PAKDD'19 Most Influential Paper Award.

This seminar will also be available via Zoom.

This event is supported by the NIGMS of the National Institutes of Health under Award Number P20GM139768. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.