Application of Machine Learning and Bioinformatics in Gene Expression Studies by FAU Student, Perry A. LaBoone

Perry A. LaBoone, currently a Ph.D. candidate in Computer Science Engineering at Florida Atlantic University, and his advisor, Dr. Raquel Assis, Associate Dean and Associate Professor in the College of Engineering and Computer Science, have recently made significant contributions to the field of gene expression through their latest publication. LaBoone, who holds a diverse academic and professional background, has applied his extensive engineering, business, and accounting skills to tackle complex problems in bioinformatics under the expert guidance of Dr. Assis.  

LaBoone began his academic journey with a B.S. in Electrical Engineering from the University of Florida, supported by an ROTC scholarship. After graduation, he served in the Navy Civil Engineer Corps, followed by roles in construction, public works, and contract management. He pursued graduate studies in the Navy, obtaining his M.S. in Computer Engineering from FAU and later an MBA and a Master of Accountancy from the University of North Florida. LaBoone's professional career included significant roles at the Department of Defense and various software consulting firms, including Sun Microsystems, Microsoft, Accenture, and Avanade, where he honed his leadership and technical skills by leading software development solutions. Although he experienced great success in industry, LaBoone always intended to return to academia to pursue a Ph.D., driven by his core identity as an engineer who thrives on solving complex problems through disciplined approaches. This ambition led him to enroll at FAU, where he chose the data science track of computer science engineering. There, he took his initial class, Introduction to Data Science, with Dr. Raquel Assis, whose teaching profoundly impacted him. His enthusiasm for the subject and Dr. Assis's guidance prompted him to join her research group in 2023, marking the beginning of a significant phase in his academic career.   

Perry A. LaBoone and Dr. Raquel Assis's recently published research explores gene expression variation in Escherichia coli  under different environmental stresses. Their research analyzed how essential genes maintain functionality when exposed to resource scarcity or antibiotics, employing sophisticated bioinformatics and data science techniques. By applying advanced statistical tools in R to flow cytometry data, they quantified variation in gene expression noise, revealing crucial insights into the cellular mechanisms that sustain life under duress. This interdisciplinary approach highlights the integration of computational methods to understand and illustrate complex biological interactions.  

Looking forward, LaBoone is poised to broaden his research scope. He is particularly enthusiastic about his forthcoming projects involving wearable technologies and artificial intelligence (AI) in healthcare. His paper, "Overview of The Future Impact of Wearables and Artificial Intelligence in Healthcare Workflows and Technology," accepted by the International Journal of Information Management Data Insights, delves into the transformative potential of wearables and AI in altering healthcare dynamics. Moreover, LaBoone is part of a pioneering effort to utilize a machine learning framework, Predicting Expression Divergence (PiXi), to model gene expression divergence between single-copy orthologs in two species. Developed with Dr. Assis and Dr. Michael DeGiorgio and PhD candidate Antara Anika Piya, PiXi integrates gene expression evolution modeling with a multi-layer neural network, showcasing an innovative approach to genetic research.  

The collaborative efforts of Perry A. LaBoone and Dr. Raquel Assis exemplify the dynamic intersection of computational methods and biological research. Their work advances our understanding of genetic mechanisms under environmental stress and sets the stage for significant healthcare innovations and biotechnological applications. As LaBoone advances in his academic career, his endeavors continue to bridge the gap between technology and biology, heralding breakthroughs in the field.    

LaBoone PA, Assis R. Stress-induced constraint on expression noise of essential genes in E. coli.  J Mol Evol , doi:10.1007/s00239-024-10211-x (2024).