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Búsqueda de genes relacionados con enfermedades con el mapeo de entidades biológicas de la literatura (MaBEL)
Gratchela Dutra Rodrigues1, Gabriel Liston de Menek1, Darling de Andrade Lourenço1
1Centro de Desenvolvimento Tecnológico, Campus Universitário, S / N - Capão do Leão, Rio Grande do Sul 96160-000, Brazil.
Computational biology and chemistry
|February 21, 2026
Resumen
MaBEL (Mapping of Biological Entities from Literature) es una plataforma de extracción de texto que identifica de manera eficiente los genes relacionados con enfermedades de diversas publicaciones científicas. Acelera el descubrimiento de posibles objetivos terapéuticos mediante el análisis de grandes cantidades de datos.
Área de la Ciencia:
- Informática biomédica La informática biomédica es un campo de la informática biomédica.
- Biología computacional Biología computacional.
- Minería de texto Minería de texto.
Sus antecedentes:
- El crecimiento exponencial de la literatura biomédica plantea desafíos para identificar genes relacionados con enfermedades y objetivos terapéuticos.
- Los sistemas de minería de texto existentes a menudo se basan en fuentes de datos únicas, lo que limita el análisis integral.
Objetivo del estudio:
- Introducir MaBEL (Mapeo de entidades biológicas a partir de la literatura), una plataforma de minería de texto escalable y adaptable.
- Unificar la recuperación de literatura, el reconocimiento de entidades y la integración de datos para el descubrimiento eficiente de la relación entre genes y enfermedades.
Principales métodos:
- MaBEL integra publicaciones de múltiples fuentes, incluidos PubMed, Scopus y servidores de preprint, utilizando la deduplicación basada en DOI.
- Emplea tuberías modulares de PNL con SciSpaCy para el reconocimiento de genes / proteínas, BioSyn para la normalización de alias y PubTator 3.0 para la anotación.
- Una arquitectura distribuida (Flask, Celery, Docker) permite el procesamiento de texto asíncrono y a gran escala.
Principales resultados:
- MaBEL procesó más de 14.000 artículos únicos para siete enfermedades principales.
- La plataforma identificó con precisión genes de alta frecuencia y salientes de enfermedades.
- Los resultados mostraron una fuerte concordancia con las puntuaciones de asociación de la Plataforma de Objetivos Abiertos, validando el descubrimiento de la relación genética de la enfermedad.
Conclusiones:
- MaBEL ofrece un marco novedoso y extensible para la minería de textos biomédicos avanzados.
- Facilita la generación rápida de hipótesis y acelera el descubrimiento de objetivos moleculares en la investigación traslacional.
- La plataforma va más allá de los enfoques estáticos de una sola base de datos para un análisis de literatura más completo.
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