Seminar Abstract:
Viral
infections are commonly observed in nature. Recently, SARS-CoV-2 has
caused a global pandemic which has infected over 200 million individuals
worldwide (as of August 2021). Effective and efficient detection of
viruses in host genomes, together with tracking how viruses interact
with host genomes, are major challenges. In this talk, I will first
introduce our computational approaches for detecting viruses and their
integration sites in host genomes from next-generation sequencing data.
Then, based on our recently developed Viral Integration Site DataBase
(VISDB), we have developed a deep learning method, DeepVISP, for virus
site integration prediction and motif discovery. To study COVID-19, we
developed a deep learning method, DrivAER: Identification of Driving
transcriptional programs with AutoEncoder derived Relevance scores from
single-cell RNA sequencing (scRNA-seq) data. We applied DrivAER to
COVID-19 scRNA-seq data and also for integrative analysis of COVID-19
genome-wide association studies (GWAS) and transcriptome-wide
association studies (TWAS). Our investigation identified a number of
genes, regulatory factors, and cellular trajectories that may be
relevant in COVID-19 disease severity.
Speaker Bio:
Dr. Zhongming Zhao has a unique, interdisciplinary educational and research background. He completed master’s degrees in Genetics (1996), Biomathematics (1998), and Computer Science (2002), Ph.D. degree in Human and Molecular Genetics (2000), and Postdoctoral Fellowship in Bioinformatics (2001 – 2003). Dr. Zhao currently serves as Chair Professor for Precision Health at UTHealth. Before he joined UTHealth in 2016, he was Ingram Endowed Professor of Cancer Research, Professor (tenured) in the Departments of Biomedical Informatics, Psychiatry, and Cancer Biology at Vanderbilt University Medical Center, Chief Bioinformatics Officer of the Vanderbilt-Ingram Cancer Center (VICC), and Associate Director of the Vanderbilt Center for Quantitative Sciences. Dr. Zhao has broad interests in bioinformatics, genomics, precision medicine, and machine learning and has co-authored more than 400 scientific papers in these areas (H-index = 68, Google Scholar). Throughout his career, he has collaborated with numerous researchers while also pursuing his own independent research, funded by numerous federal, state, and foundation grants. He has trained more than 70 students and postdoctoral fellows (24 have become academic faculty), mentored 11 junior faculty, and co-mentored/collaborated with five NIH K awardees. For more information see attached flyer.
Zoom Details:
Link: https://hawaii.zoom.us/j/91648942759
Meeting ID: 916 4894 2759 Passcode: BIOM646
