Mondrian Map: Piet Mondrian's Abstraction for Differential Pathway Analysis.

Motivation:Visualizing complex biological networks is a significant challenge, as traditional tools often struggle to represent data clearly and intuitively. Drawing inspiration from Piet Mondrian's abstract art style, we introduce Mondrian Map, a novel visualization tool that transforms the complexity of biological networks into a more organized, meaningful, and aesthetically appealing form. Results:In our case study of glioma progression, Mondrian Map reveals distinct pathway patterns across multiple patient profiles at different time points. Afterwards, the significance of these distinctive pathways in glioblastoma multiforme development is validated by recent literature. Mondrian Map's visually intuitive representation of complex biological networks enables researchers to easily identify crucial pathways and potential therapeutic targets. Moreover, The potential applications of Mondrian Map extend beyond biology, making it a versatile tool across domains. Availability and Implementation:The code was implemented in Python version 3.10 and is available through GitHub (github.com/fuad021/mondrian-map). The datasets used in this paper were retrieved from Glioma Longitudinal AnalySiS (GLASS) consortium.