Institute of Robotics and Automatic Information System
Seminar Series：Advanced Robotics & MEMS
题目：生物医学研究中的计算方法Computational Approaches in Biomedical Research
单位：Department of Pediatrics- Neurology, Baylor College of Medicine, USA （美国 贝勒医学院儿科神经系）
上午报告Seminar 10:00-10:40 会后讨论Post-Workshop 11:00-11:20
Abstract: High throughput technology, such microarray and next-generation sequencing, has revolutionized the field of biomedical research. However, there is still a big gap between data collection and understanding the complexity of the underlying biology. Bioinformatics is becoming a central part of the biomedical research. In this talk, I will describe our recent studies to understand the complex high dimensional biological data using statistical learning approaches, such as regression based deconvolution, Markov network on exponential family distribution and Graph Laplacian penalized feature selection algorithm. In addition, I will discuss our most recent findings on the data reproducibility issue in the Cancer Genome Atlas project.
Bio: Dr. Liu has been an Assistant Professor in the Department of Pediatrics-Neurology at Baylor College of Medicine since 2010. Prior to that, he worked at University of Pennsylvania as a post-doctoral fellow for one year. He obtained his Bachelor"s degree in Computer science from Nankai University in 2001, and received his PhD from the University of Pennsylvania in 2009. Dr. Liu’s research interests focus on developing bioinformatics approaches for analyzing high-throughput biological data produced by gene expression arrays, RNA-seq and genomic sequencing. His work integrates multiple data types in the interest of advancing our understanding of neurological diseases. Dr. Liu has published papers about bioinformatics in leading journals such as Nature Methods, PNAS, NIPS, Genome Biology, and Nucleic Acids Research. He is also a member of International Society of Computational Biology.