Prof. Zhongming Zhao (Fellow of ACMI, AMIA and AIMBE)
The University of Texas Health Science Center at Houston, USA
Dr. Zhongming Zhao is the director of the Center for Precision Health, the University of Texas Health Science Center at Houston (UTHealth). Before he joined UTHealth in 2016, he was Ingram Endowed Professor of Cancer Research, Professor in the Departments of Biomedical Informatics, Psychiatry, and Cancer Biology at Vanderbilt University Medical Center, and Chief Bioinformatics Officer of the Vanderbilt-Ingram Cancer Center (VICC). Dr. Zhao has broad interests in bioinformatics, genomics, and computational biology, and he has co-authored over 450 total publications in these areas (H-index = 76). Dr. Zhao is an elected fellow of the American College of Medical Informatics (ACMI), the American Medical Informatics Association (FAMIA), the American Institute for Medical and Biological Engineering (AIMBE).
Speech Title: "Mining Multi-omics Data for Accurate Drug Response Prediction"
Abstract: There have been massive amounts of multi-omics data for drug response ranging from cell lines, human and animal studies, and clinical trials. Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Transcriptome context, especially in tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this talk, I will first review several approaches to identification of cancer driver and actional mutations. Then, I will introduce a recently developed deep variational autoencoder model followed by Elastic Net strategy (VAEN) for accurate drug response prediction. VAEN compress thousands of genes into latent vectors in a low-dimensional space. We demonstrate that these encoded vectors could accurately impute cancer drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. Using the well-trained models, we imputed drug response of The Cancer Genome Atlas (TCGA) data and investigate the features and signatures associated with the imputed drug response.
Prof. Xiyin Wang
North China University of Science and Technology, China
Xiyin Wang received the PhD in Bioinformatics, Beijing University, 2005. He is Professor and Dean at the School of Life Science (2010-2019) and School of Science (2019) in the North China University of Science and Technology, China. His major achievements are in Chromosome evolution and reduction theory, the origin of B chromosomes, plant genome structure and evolution, plant polyploidy, and proposition of gold standard to decipher complex plant genomes. Developing bioinformatics software WGDI, ColinearScan, and MCScan, and databases PGDD, GGDB, etc. He was elected as the top scientists in Biology and biochemistry.
Speech Title: "Plant Chromosome History Reconstruction"
Abstract: Based on the genomics model of plant chromosome evolution and bioinformatics methods and software mainly previously proposed by the author and colleagues, we are conducting in-depth analysis of the sequenced plant genome sequence, and plan to reconstruct the main ancestor nodes in the process of plant evolution. The so-called telomere-central model described chromosome arrangements, which occur in mainly three ways, nested-chromosome fusion, end-end joining of chromosomes, and arm exchange between chromosomes. Chromosome number reduction is indispensably accompanied by the production of B chromosomes, consisting two telomeres from one or two chromosomes. For nested chromosome fusion, one ancestral chromosome initially forms a circular one by crossing-over near its two telomeres, and a resolution of the Holiday structure results in a telomere-free or free-end chromosome and a B chromosome; then the free-end chromosome is nested into another chromosome, and the B chromosome will be lost.