An LLM-Based Tool for Automated Generation of 3D Model Organism Colony Simulations

We present MicroVerse, a software application based on large language models (LLMs) designed to generate C# scripts simulating three-dimensional colonies of model organisms, including <i>Escherichia coli</i> and <i>Saccharomyces cerevisiae</i>, within the Unity platform. The system, which utilizes fine-tuned LLMs, translates descriptions of desired simulations (organizations, growth rates, and appearance) in natural language into functional C# code. The coupling of artificial intelligence with biological simulation generates intricate dynamics to be simulated. The approach involves using a dual-LLM pipeline (one computing user requests, the other generating code for Unity Data-Oriented Technology Stack (DOTS)), with the goal of making 3D simulation development more democratized. It provides a scalable, customizable option, particularly for users lacking sophisticated programming skills, decreasing manual coding effort and time. This work explains the pipeline architecture and fine-tuning process and demonstrates the system successfully producing functional, scalable simulations, scaling up to cases with more than one million organisms.

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Publication Details

Journal
ACS Synthetic Biology
Published
2025-11-10
DOI
https://doi.org/10.1021/acssynbio.5c00402
Primary Topic
Gene Regulatory Network Analysis
Type
article
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article

An LLM-Based Tool for Automated Generation of 3D Model Organism Colony Simulations

Martín Gutiérrez, Tobías Guerrero Cheuquepán, Iván Cáceres Satorres, Bastián Castro Salazar et al.
ACS Synthetic Biology
Gene Regulatory Network Analysis
article

An LLM-Based Tool for Automated Generation of 3D Model Organism Colony Simulations

Martín Gutiérrez, Tobías Guerrero Cheuquepán, Iván Cáceres Satorres, Bastián Castro Salazar, Brian Castro Farías
article en

Abstract

We present MicroVerse, a software application based on large language models (LLMs) designed to generate C# scripts simulating three-dimensional colonies of model organisms, including <i>Escherichia coli</i> and <i>Saccharomyces cerevisiae</i>, within the Unity platform. The system, which utilizes fine-tuned LLMs, translates descriptions of desired simulations (organizations, growth rates, and appearance) in natural language into functional C# code. The coupling of artificial intelligence with biological simulation generates intricate dynamics to be simulated. The approach involves using a dual-LLM pipeline (one computing user requests, the other generating code for Unity Data-Oriented Technology Stack (DOTS)), with the goal of making 3D simulation development more democratized. It provides a scalable, customizable option, particularly for users lacking sophisticated programming skills, decreasing manual coding effort and time. This work explains the pipeline architecture and fine-tuning process and demonstrates the system successfully producing functional, scalable simulations, scaling up to cases with more than one million organisms.

ACS Synthetic BiologyVol. 14(11)
Universidad Diego Portales (CL)
Openalex Percentile: Top 70%
Gene Regulatory Network Analysis
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