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Pattern-based Search of Epigenomic Data Using GeNemo

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Diseño semántico: Programación de genes funcionales a partir del contexto genómico

Yulin Huang¹, Ping Lin¹

¹Biological Science Research Center, Integrative Science Center of Germplasm Creation in Western China (Chongqing) Science City, Chongqing Technology Innovation Center of Breeding, Academy for Advanced Interdisciplinary Studies, Southwest University, Chongqing 400715, China.

|January 10, 2026

Resumen

Este resumen es generado por máquina.

El diseño semántico utiliza el modelo de lenguaje genómico Evo para crear genes funcionales novedosos a partir del contexto genómico. La base de datos SynGenome contiene más de 120 mil millones de secuencias de este tipo para diversas aplicaciones biológicas.

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Área de la Ciencia:

Genómica
Biología Sintética
Bioinformática

Sus antecedentes:

Los modelos genómicos generativos ofrecen potencial para el diseño de sistemas biológicos.
El diseño preciso de secuencias de genes funcionales sigue siendo un desafío importante.

Objetivo del estudio:

Introducir el diseño semántico para la generación de genes funcionales novedosos.
Aprovechar el modelo de lenguaje genómico Evo para el diseño de secuencias.
Establecer la base de datos SynGenome para albergar las secuencias generadas.

Principales métodos:

Empleo del modelo de lenguaje genómico Evo.
Utilización del contexto genómico para la generación de secuencias.
Desarrollo de la base de datos SynGenome.

Principales resultados:

Generación exitosa de genes funcionales novedosos utilizando diseño semántico.
Creación de la base de datos SynGenome con más de 120 mil millones de secuencias.
Demostración de diversas capacidades funcionales dentro de las secuencias generadas.

Conclusiones:

El diseño semántico proporciona un enfoque poderoso para la generación de genes funcionales.
La base de datos SynGenome representa un recurso importante para la biología sintética y la investigación genómica.