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A comparison of graph- and kernel-based –omics data integration algorithms for classifying complex traits
BACKGROUND: High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order to provid...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2017
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389230/ https://www.ncbi.nlm.nih.gov/pubmed/29212468 http://dx.doi.org/10.1186/s12859-017-1982-4 |