Jacek Grzebyta
Papers
1
Total Citations
32
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1
About
Jacek Grzebyta is a systems biologist whose work lies at the intersection of computational modeling, experimental design, and automation. His primary research focuses on developing closed-loop frameworks that integrate experiment planning, execution, and machine learning to accelerate biological discovery. His most cited work, “Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast” (2019, 32 citations), exemplifies this approach. In this study, Grzebyta and colleagues used the yeast diauxic shift as a model system, iteratively refining a computational model through three cycles: first, building a model that outperformed existing ones using bioinformatics and systems biology tools; second, improving it via automatically planned experiments; and third, testing hypothesis-driven experiments. This work demonstrates a powerful paradigm for reducing the time and cost of model development in complex biological systems. Grzebyta’s contributions highlight the potential of integrating automation and machine learning into systems biology, offering a template for future research in dynamic cellular processes.
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