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

Daniel R. Bergman; Jeanette A.I. Johnson; Marwa Naji; Max Booth; Heber Lima da Rocha; Atul Deshpande; Dimitrios N. Sidiropoulos; Tamara Lopez-Vidal; Randy Heiland; Luciane T. Kagohara; Robert A. Anders; Lei Zheng; Elizabeth M. Jaffee; Genevieve Stein-O’Brien; Paul Macklin; Elana J. Fertig

doi:10.1093/bioinformatics/btaf571

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

Daniel R. Bergman
, Jeanette A.I. Johnson
, Marwa Naji
, Max Booth
, Heber Lima da Rocha
, Atul Deshpande
, Dimitrios N. Sidiropoulos
, Tamara Lopez-Vidal
, Randy Heiland
, Luciane T. Kagohara
, Robert A. Anders
, Lei Zheng
, Elizabeth M. Jaffee
, Genevieve Stein-O’Brien
, Paul Macklin
, Elana J. Fertig

Producción científica: Article › revisión exhaustiva

Resumen

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.

Idioma original	English (US)
Número de artículo	btaf571
Publicación	Bioinformatics
Volumen	41
N.º	11
DOI	https://doi.org/10.1093/bioinformatics/btaf571
Estado	Published - nov 1 2025
Publicado de forma externa	Sí

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btaf571

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Bergman, D. R., Johnson, J. A. I., Naji, M., Booth, M., Lima da Rocha, H., Deshpande, A., Sidiropoulos, D. N., Lopez-Vidal, T., Heiland, R., Kagohara, L. T., Anders, R. A., Zheng, L., Jaffee, E. M., Stein-O’Brien, G., Macklin, P., & Fertig, E. J. (2025). BIWT: a bioinformatics walkthrough for embedding spatial multiomics in agent-based models for virtual cells. Bioinformatics, 41(11), Artículo btaf571. https://doi.org/10.1093/bioinformatics/btaf571

Bergman, DR, Johnson, JAI, Naji, M, Booth, M, Lima da Rocha, H, Deshpande, A, Sidiropoulos, DN, Lopez-Vidal, T, Heiland, R, Kagohara, LT, Anders, RA, Zheng, L, Jaffee, EM, Stein-O’Brien, G, Macklin, P & Fertig, EJ 2025, 'BIWT: a bioinformatics walkthrough for embedding spatial multiomics in agent-based models for virtual cells', Bioinformatics, vol. 41, n.º 11, btaf571. https://doi.org/10.1093/bioinformatics/btaf571

@article{d465cc6642af4285913db311c483b7c8,

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

abstract = "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.",

author = "Bergman, \{Daniel R.\} and Johnson, \{Jeanette A.I.\} and Marwa Naji and Max Booth and \{Lima da Rocha\}, Heber and Atul Deshpande and Sidiropoulos, \{Dimitrios N.\} and Tamara Lopez-Vidal and Randy Heiland and Kagohara, \{Luciane T.\} and Anders, \{Robert A.\} and Lei Zheng and Jaffee, \{Elizabeth M.\} and Genevieve Stein-O{\textquoteright}Brien and Paul Macklin and Fertig, \{Elana J.\}",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025. Published by Oxford University Press.",

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doi = "10.1093/bioinformatics/btaf571",

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AU - Bergman, Daniel R.

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AU - Lima da Rocha, Heber

AU - Deshpande, Atul

AU - Sidiropoulos, Dimitrios N.

AU - Lopez-Vidal, Tamara

AU - Heiland, Randy

AU - Kagohara, Luciane T.

AU - Anders, Robert A.

AU - Zheng, Lei

AU - Jaffee, Elizabeth M.

AU - Stein-O’Brien, Genevieve

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AU - Fertig, Elana J.

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AB - 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.

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

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ASJC Scopus subject areas

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