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    La inteligencia artificial (IA) y el aprendizaje automático están revolucionando la investigación de la microbiología y el microbioma. Estos métodos computacionales avanzados ofrecen herramientas potentes para comprender la vida microbiana y su impacto en la salud y el medio ambiente.

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    Área de la Ciencia:

    • Microbiología
    • Investigación del Microbioma
    • Bioinformática

    Sus antecedentes:

    • La inteligencia artificial (IA) está impactando cada vez más la investigación científica.
    • El aprendizaje automático (ML) y el aprendizaje profundo (DL) son técnicas clave de IA.
    • Estos métodos están impulsando avances en los estudios de microbiología y microbioma.

    Objetivo del estudio:

    • Proporcionar una visión general completa de los enfoques impulsados por la IA en la investigación de la microbiología y el microbioma.
    • Detallar las técnicas fundamentales de IA y sus aplicaciones.
    • Discutir los desafíos y los avances recientes en el campo.

    Principales métodos:

    • Revisión de la literatura existente sobre aplicaciones de IA en la investigación de microbiología y microbioma.
    • Explicación de las técnicas fundamentales de IA (ML, DL).
    • Categorización de las aplicaciones de IA en diversas áreas de investigación.

    Principales resultados:

    • La IA permite avances en el perfil taxonómico, la anotación funcional y la predicción.
    • La IA facilita el estudio de las interacciones microbio-X, la ecología microbiana y el modelado metabólico.
    • Las aplicaciones de la IA se extienden a la nutrición de precisión, la microbiología clínica, la prevención y la terapéutica.

    Conclusiones:

    • La IA juega un papel transformador en la investigación de la microbiología y el microbioma.
    • Las metodologías de IA mejoran nuestra comprensión de la vida microbiana y su impacto global.
    • La integración de la IA promete aplicaciones innovadoras para la ciencia de la salud y el medio ambiente.