BIWT: a bioinformatics walkthrough for embedding spatial multiomics in agent-based models for virtual cells

作者：Daniel Bergman, Jeanette Johnson, Marwa Naji, Max Booth, Heber L. Rocha, Atul Deshpande, Dimitrios N. Sidiropoulos, Tamara Y. Lopez-Vidal, Randy Heiland, Luciane T. Kagohara, Robert A. Anders, Lei Zheng, Elizabeth M. Jaffee, Genevieve Stein-O’Brien, Paul Macklin, Elana J. Fertig · 发表于：Bioinformatics · 年份：2025 · DOI：10.1093/bioinformatics/btaf571 · 被引用次数：1 · 研究领域：Single-cell and spatial transcriptomics、Mathematical Biology Tumor Growth、Cancer Genomics and Diagnostics

SUMMARY: Whereas transcriptomic and spatial profiling offer static snapshots of tissue structure, mechanistic models use biological rules to predict how tissues evolve. We present the BioInformatics WalkThrough (BIWT) software to directly initialize spatial agent-based models from single-cell and spatial molecular data. We demonstrate how initialization strategies affect tumor-immune dynamics and spatial clustering, positioning BIWT as a software suite to generate data-driven virtual cells representing both experimental and clinical contexts. AVAILABILITY AND IMPLEMENTATION: The BIWT software is available at https://github.com/PhysiCell-Tools/PhysiCell-Studio. The sample dataset for running the BIWT is available at https://zenodo.org/records/16365625. The code and instructions for reproducing the use case example is available at https://github.com/drbergman/BIWT-Paper.