A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism

BACKGROUND: Machine learning approaches for predicting disease risk from high-dimensional whole genome sequence (WGS) data often result in unstable models that can be difficult to interpret, limiting the identification of putative sets of biomarkers. Here, we design and validate a graph-based method...

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Detalles Bibliográficos
Autores principales: Varma, Maya, Paskov, Kelley M., Chrisman, Brianna S., Sun, Min Woo, Jung, Jae-Yoon, Stockham, Nate T., Washington, Peter Y., Wall, Dennis P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091705/
https://www.ncbi.nlm.nih.gov/pubmed/33941233
http://dx.doi.org/10.1186/s13040-021-00262-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091705/
https://www.ncbi.nlm.nih.gov/pubmed/33941233
http://dx.doi.org/10.1186/s13040-021-00262-x

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