Artículo
Using prior knowledge in the inference of gene association networks
Autor/es | Nepomuceno Chamorro, Isabel de los Ángeles
Nepomuceno Chamorro, Juan Antonio Galván Rojas, José Luis Vega Márquez, Belén Rubio Escudero, Cristina |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2020 |
Fecha de depósito | 2022-05-27 |
Publicado en |
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Resumen | Traditional computational techniques are recently being improved with the use of prior biological knowledge from open access repositories in the area of gene expression data analysis. In this work, we propose the use of ... Traditional computational techniques are recently being improved with the use of prior biological knowledge from open access repositories in the area of gene expression data analysis. In this work, we propose the use of prior knowledge as heuristic in an inference method of gene-gene associations from gene expression profiles. In this paper, we use Gene Ontology, which is an open-access ontology where genes are annotated using their biological functionality, as a source of prior knowledge together with a gene pairwise Gene-Ontology-based measure. The performance of our proposal has been compared to other benchmark methods for the inference of gene networks, outperforming in some cases and obtaining similar and competitive results in others, but with the advantage of providing simple and interpretable models, which is a desired feature for the Artificial Intelligence Health related models as stated by the European Union. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España |
Identificador del proyecto | TIN2017-88209-C2-2-R |
Cita | Nepomuceno Chamorro, I.d.l.Á., Nepomuceno Chamorro, J.A., Galván Rojas, J.L., Vega Márquez, B. y Rubio Escudero, C. (2020). Using prior knowledge in the inference of gene association networks. Applied Intelligence, 50 (11), 3882-3893. |
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