2022 Undergraduate Research Symposium Abstract, Ahmad Mersaghian and Sarron Tadesse

A New Gene Expression Dataset for GRNsight: a Web Application for Visualizing Gene Network Models

Ahmad R. Mersaghian, Sarron A. Tadesse, John David N. Dionisio, Kam D. Dahlquist

Department of Computer Science, Department of Biology, Loyola Marymount University, 1 LMU Drive, Los Angeles, CA 90045 USA

GRNsight is an open-source web application and service for visualizing models of gene regulatory networks (GRNs). A gene regulatory network consists of genes, transcription factors, and the regulatory connections between them which govern the level of expression of mRNA and protein from genes. GRNmap is a MATLAB program that performs parameter estimation and forward simulation of a differential equations model of a GRN based on user-provided expression data. GRNsight reads Microsoft Excel input and output workbooks from GRNmap and automatically displays the model data as a graph. Graph edges are color-coded based on the activation and repression relationships between the transcription factors, and nodes are color-coded with time course gene expression data provided by the user or retrieved from the backend database. To expand the potential research scope, a new expression dataset was chosen to be added to the GRNsight database. Apweiler et al. (2012) measured gene expression changes over time in Saccharomyces cerevisiae due to adding glucose to the media. To clean this dataset for inclusion in the database, we needed to remove duplicate data and assign the correct ID types. To further analyze the data with GRNmap, we clustered with STEM to identify significant expression profiles and inferred the gene regulatory network with YEASTRACT. After running GRNmap, we visualized the results of the model using GRNsight. In parallel, ongoing development of GRNsight is focused on fixing bugs and adding enhancements to the user interface and graph layout. GRNsight is freely available at http://dondi.github.io/GRNsight/.