Presentation Title

Restructuring the Data Architecture of GRNmap, a Gene Regulatory Network Modeling Application

Faculty Mentor

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

Start Date

18-11-2017 2:15 PM

End Date

18-11-2017 3:15 PM

Location

BSC-Ursa Minor 124

Session

Poster 3

Type of Presentation

Poster

Subject Area

interdisciplinary

Abstract

A gene regulatory network (GRN) consists of a set of transcription factors that regulate the level of expression of genes encoding other transcription factors. The dynamics of a GRN describe how gene expression in the network changes over time. GRNmap is a complex MATLAB software package that uses ordinary differential equations to model the dynamics of small- to medium-scale GRNs. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on DNA microarray data, using forward simulations of model dynamics. Input is provided in the form of a multisheet Excel workbook with multiple types of data. Since our last major release, we have improved GRNmap’s usability and robustness. We changed our simple matrix into a nested cell array of matrices to handle inputs with missing values, which required a paradigm shift in our data structure. Additionally, we revisited design, implemented new features, fixed bugs, expanded the test suite, and improved documentation. We localized extraneous global variables by grouping them into a single function call to limit their scope and prevent persistence between subsequent runs, which previously led to incorrect calculations. Finally, we implemented pre-allocation of arrays which makes the program run faster as MATLAB no longer needs to calculate matrix sizes at runtime and ensures matrix operations work smoothly as this method clears previously used data to prevent persistence between runs of differently-sized networks. The open source code and executable are available for download at http://kdahlquist.github.io/GRNmap/ under the BSD license.

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Nov 18th, 2:15 PM Nov 18th, 3:15 PM

Restructuring the Data Architecture of GRNmap, a Gene Regulatory Network Modeling Application

BSC-Ursa Minor 124

A gene regulatory network (GRN) consists of a set of transcription factors that regulate the level of expression of genes encoding other transcription factors. The dynamics of a GRN describe how gene expression in the network changes over time. GRNmap is a complex MATLAB software package that uses ordinary differential equations to model the dynamics of small- to medium-scale GRNs. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on DNA microarray data, using forward simulations of model dynamics. Input is provided in the form of a multisheet Excel workbook with multiple types of data. Since our last major release, we have improved GRNmap’s usability and robustness. We changed our simple matrix into a nested cell array of matrices to handle inputs with missing values, which required a paradigm shift in our data structure. Additionally, we revisited design, implemented new features, fixed bugs, expanded the test suite, and improved documentation. We localized extraneous global variables by grouping them into a single function call to limit their scope and prevent persistence between subsequent runs, which previously led to incorrect calculations. Finally, we implemented pre-allocation of arrays which makes the program run faster as MATLAB no longer needs to calculate matrix sizes at runtime and ensures matrix operations work smoothly as this method clears previously used data to prevent persistence between runs of differently-sized networks. The open source code and executable are available for download at http://kdahlquist.github.io/GRNmap/ under the BSD license.