Predictions Generated from a Simulation Engine for Gene Expression Micro-arrays for use in Research Laboratories

Authors

Gopinath R. Mavankal, Southern Methodist UniversityFollow
John Blevins, Southern Methodist UniversityFollow
Dominique Edwards, Southern Methodist UniversityFollow
Monnie McGee, Southern Methodist UniversityFollow
Andrew Hardin, To be providedFollow

Abstract

In this paper we introduce the technical components, the biology and data science involved in the use of microarray technology in biological and clinical research. We discuss how laborious experimental protocols involved in obtaining this data used in laboratories could benefit from using simulations of the data. We discuss the approach used in the simulation engine from [7]. We use this simulation engine to generate a prediction tool in Power BI, a Microsoft, business intelligence tool for analytics and data visualization [22]. This tool could be used in any laboratory using micro-arrays to improve experimental design by comparing how predicted signal intensity compares to observed signal intensity. Signal intensity in micro-arrays is a proxy for level of gene expression in cells. We suggest further development avenues for the prediction tool.

Recommended Citation

Mavankal, Gopinath R.; Blevins, John; Edwards, Dominique; McGee, Monnie; and Hardin, Andrew (2018) "Predictions Generated from a Simulation Engine for Gene Expression Micro-arrays for use in Research Laboratories," SMU Data Science Review: Vol. 1: No. 2, Article 9.
Available at: https://scholar.smu.edu/datasciencereview/vol1/iss2/9

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License