Merging logical models: An application in Acute Myeloid Leukemia modeling.

Abstract

Gene regulatory network (GRNs) models provide mechanistic understanding of the gene regulations and interactions that control various aspects of cellular behaviors. While researchers have constructed GRNs to model specific sets of gene regulations or interactions, little work has been made to integrate or merge these models into larger, more comprehensive ones that could encompass more genes, and improve the accuracy of predicting biological processes. Here, we present a workflow for merging logical GRN models, which requires sequential steps including model standardization, reproducing, merging and evaluations, and demonstrate its application in acute myeloid leukemia (AML) study. We demonstrate the feasibility and benefits of model merging by integrating two pairs of published models. Our integrated models were able to retain similar accuracy of the original publications, while increasing the coverage and explainability of the biological system. This approach highlights the integration of logical models in advancing system biology and enhancing the understanding of complex diseases.