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Descripción
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| Over a decade ago, a new discipline called network medicine emerged as an approach to understand human diseases from a network theory point-of-view. Disease networks proved to be an intuitive and powerful way to reveal hidden connections among apparently unconnected biomedical entities such as diseases, physiological processes, signaling pathways, and genes. One of the fields that has benefited most from this improvement is the identification of new opportunities for the use of old drugs, known as drug repurposing. The importance of drug repurposing lies in the high costs and the prolonged time from target selection to regulatory approval of traditional drug development. In this document we analyze the evolution of disease network concept during the last decade and apply a data science pipeline approach to evaluate their functional units. As a result of this analysis, we obtain a list of the most commonly used functional units and the challenges that remain to be solved. This information can be very valuable for the generation of new prediction models based on disease networks. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Journal of Biomedical Informatics |
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ISSN
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1532-0464 |
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Factor de impacto JCR
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2,95 |
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Información de impacto
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Datos JCR del año 2018 |
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Volumen
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94 |
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DOI
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10.1016/j.jbi.2019.103206 |
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Número de revista
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Desde la página
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103206 |
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Hasta la página
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103206 |
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Mes
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JUNIO |
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Ranking
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