John Lopez 2018 SURP Abstract

Implementing Dynamic Gene Webpages for GRNsight: a Web Application for Visualizing Models of Gene Regulatory Networks

John L. Lopez, Kam D. Dahlquist, John David N. Dionisio, and Ben G. Fitzpatrick

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

GRNsight is a 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, a MATLAB program that performs parameter estimation and forward simulation of a differential equations model of a GRN, can mathematically model GRNs. Using GRNmap output spreadsheets, GRNsight automatically lays out the network graph through a force simulation or in a grid. GRNsight uses pointed and blunt arrowheads on the edges and color-codes and adjusts edge thicknesses based on the sign (activation or repression) and magnitude of the GRNmap weight parameter. Nodes are colored based on experimental or simulated time course gene expression data found in the GRNmap spreadsheet. I have now implemented a dynamic gene information webpage that opens when a user right-clicks on a node in the graph. The page sends a series of Asynchronous JavaScript and XML (AJAX) data requests, written using the jQuery JavaScript library, to the JASPAR, NCBI Gene, UniProt, Ensembl, and Saccharomyces Genome Databases. The webpage is then populated with data returned regarding the gene’s description, protein sequence, DNA binding motif frequency matrix and sequence logo, and Gene Ontology terms. The page was styled using the Bootstrap Cascading Style Sheets library. This new feature enables users to easily access information about the genes to facilitate biological interpretation of the GRN data, and is available in GRNsight version 3.1.0 at http://dondi.github.io/GRNsight.

Word Count: 248