{"ok":true,"nota":{"id":"4cdb1efd1b87e9a0","slug":"un-nuevo-metodo-combina-datos-de-varios-estudios-para-encontrar-patron-4cdb1e","titulo":"Un nuevo método combina datos de varios estudios para encontrar patrones biológicos más confiables","resumen":"Presentaron MINT Block, un marco que integra datos multi-ómicos de estudios independientes corrigiendo a la vez las diferencias entre ellos. Según los autores, evita distorsionar las señales biológicas que se busca encontrar.","fuente":"biorxiv","fuenteNombre":"bioRxiv · preprints","color":"#be2628","autor":"Hirst, D. P., Terzin, M., Burnard, S. M., Le Cao, K.-A.","url":"https://www.biorxiv.org/content/10.64898/2026.10.13.758954v1?rss=1","imagen":"/hoy/portada/4cdb1efd1b87e9a0","tema":"ciencia","subtemas":["multi-omica","estadistica biologica","marcadores moleculares","integracion de datos","biomedicina"],"entidades":["MINT Block","bioRxiv"],"formato":"dato","entretenimiento":false,"pubTs":"2026-10-20T00:00:00.000Z","indexTs":"2026-10-20T12:15:39.527Z","hash":"b544d2c452dc317b662c4a2dc09b6d9244de65c37cab8348b0b02e2939e9ac68","tsa":{"time":"Oct 20 12:17:09 2026 GMT","provider":"freetsa.org"},"stats":{"views":0,"likes":0,"clicks":0,"dwell":0},"tipo":"normal","registro":"hallazgo","porQueImporta":"Muchos estudios médicos tienen muestras chicas, y juntar datos de varios equipos ayuda pero también mete ruido que puede esconder lo importante. Un método que separa ese ruido sin borrar la señal biológica acelera la búsqueda de marcadores de enfermedades. Para la investigación médica argentina, que trabaja con recursos limitados, aprovechar mejor lo que ya se midió puede significar más resultados sin empezar de cero.","quienFirma":"bioRxiv · preprints","confianza":"preprint","consulta":null},"sello":{"hash":"b544d2c452dc317b662c4a2dc09b6d9244de65c37cab8348b0b02e2939e9ac68","sello":null,"beacon":null,"verificacion":null,"tsa":{"time":"Oct 20 12:17:09 2026 GMT","provider":"freetsa.org"},"original":{"titulo":"MINT Block: multivariate integration across independent studies to identify multi-omics signatures","descripcion":"Integrative multi-omics analyses can identify molecular signatures spanning multiple layers of a biological system. However, signatures derived from datasets with small sample sizes may not generalise. Combining data from multiple independent studies can increase the available sample size, but may also introduce unwanted variation arising from study-specific differences. Existing approaches typically address this variation sequentially by correcting the data before downstream model fitting, which can inadvertently distort the biological signals of interest. We introduce MINT Block, a framework that integrates multi-omics data across independent studies while simultaneously accounting for stu","pubDate":"2026-10-20","url":"https://www.biorxiv.org/content/10.64898/2026.10.13.758954v1?rss=1"},"indexado":"2026-10-20T12:15:39.527Z"}}