Development of a novel computational technique to create DNA and cell geometrical models for Geant4-DNA
DNA geometries
Monte carlo simulations
Geant4-DNA
Radiation biology
610
[SDV.CAN]Life Sciences [q-bio]/Cancer
DNA damage response
Geant4-DNA DNA geometries DNA damage response Monte Carlo simulations
Monte Carlo simulations
DOI:
10.1016/j.ejmp.2024.104839
Publication Date:
2024-10-25T11:00:08Z
AUTHORS (7)
ABSTRACT
This study aimed to develop a novel human cell geometry for the Geant4-DNA simulation toolkit that explicitly incorporates all 23 chromosome pairs of the human cell. This approach contrasts with the existing, default human cell, geometrical model, which utilizes a continuous Hilbert curve.A Python-based tool named "complexDNA" was developed to facilitate the design of both simple and complex DNA geometries. This tool was employed to construct a human cell geometry with individual pairs of chromosomes. Subsequently, the performance of this chromosomal model was compared to the standard human cell model provided in the "molecularDNA" Geant4-DNA example.Simulations using the new chromosomal model revealed minimal discrepancies in DNA damage yield and fragment size distribution compared to the default human cell model. Notably, the chromosomal model demonstrated significant computational efficiency, requiring approximately three times less simulation time to achieve equivalent results.This work highlights the importance of incorporating chromosomal structure into human cell models for radiation biology research. The "complexDNA" tool offers a valuable resource for creating intricate DNA structures for future studies. Further refinements, such as implementing smaller voxels for euchromatin regions, are proposed to enhance the model's accuracy.
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