SEMINAR: Plant Genotype-Phenotype (G2P) Association Discovery via Integrative Genome-scale Biological Network and Genome-wide Association Analysis

Understanding the genotype and phenotype (G2P) associations has been an important and challenging task in biology. Genome-wide analysis of regulatory networks (GRNs) is one of the keys towards understanding plant developmental, stress-resistance and disease-resistance mechanisms. In the first part of my seminar, I will present our recently developed methods and tools, including our psRNATarget Web Server ( and GPLEXUS Web Server (, for the construction of large-scale transcriptional regulatory networks and analysis of subnetworks /functional modules. Complex plant traits, such as yield, tolerance to abiotic and biotic stresses, are often governed by many individual genes (G), the gene-gene interactions (GxG) and gene-environment interactions (GxE). Therefore, analysis of complex plant trait demands accurately dissecting these genetic causal effects consistently associated with the observed phenotypes. In the second part of my talk, I will present our ongoing development of a trio of genotype-phenotype association analysis tools, namely 1) GWASPRO (; 2) PEPIS (; and 3) PATOWAS (, which further extends the linear mixed models (LMMs) for genome-wide association studies (GWASs) for broader associative ‘omics’ studies.
When Apr 20, 2018
from 03:00 PM to 04:30 PM
Where Duthie 117
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Dr. Patrick X. Zhao is a Professor of Computational Biology and Bioinformatics at the Noble Research Institute ( (formerly known as the Samuel Robert Noble Foundation or the Noble Foundation; our organization’s name was changed on May 10, 2017 to Noble Research Institute). After graduation, he joined Dr. Eugenia Wang’s Lab in the School of Medicine, University of Louisville, Kentucky, USA, first as a Postdoctoral Fellow and then as a Bioinformatics Research Associate, to develop bioinformatics methods and tools for the discovery of genes and biological networks essential to the determination of the normal aging process and in particular those related to successful aging in centenarians. Dr. Zhao’s current research centers on Computational Biology and Bioinformatics, Statistics and Machine Learning for big bio-data analysis and biological knowledge discovery, and their applications in plant and soil microbe functional genomics and comparative ‘omics’.