iOmicsPASS: network-based integration of multiomics data for predictive subnetwork discovery

Computational tools for multiomics data integration have usually been designed for unsupervised detection of multiomics features explaining large phenotypic variations. To achieve this, some approaches extract latent signals in heterogeneous data sets from a joint statistical error model, while othe...

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Detalles Bibliográficos
Autores principales: Koh, Hiromi W. L., Fermin, Damian, Vogel, Christine, Choi, Kwok Pui, Ewing, Rob M., Choi, Hyungwon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Technology Feature
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616462/
https://www.ncbi.nlm.nih.gov/pubmed/31312515
http://dx.doi.org/10.1038/s41540-019-0099-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616462/
https://www.ncbi.nlm.nih.gov/pubmed/31312515
http://dx.doi.org/10.1038/s41540-019-0099-y

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