Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases

BACKGROUND: Clinical interpretation of genetic variants in the context of the patient’s phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interp...

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Detalles Bibliográficos
Autores principales: De La Vega, Francisco M., Chowdhury, Shimul, Moore, Barry, Frise, Erwin, McCarthy, Jeanette, Hernandez, Edgar Javier, Wong, Terence, James, Kiely, Guidugli, Lucia, Agrawal, Pankaj B., Genetti, Casie A., Brownstein, Catherine A., Beggs, Alan H., Löscher, Britt-Sabina, Franke, Andre, Boone, Braden, Levy, Shawn E., Õunap, Katrin, Pajusalu, Sander, Huentelman, Matt, Ramsey, Keri, Naymik, Marcus, Narayanan, Vinodh, Veeraraghavan, Narayanan, Billings, Paul, Reese, Martin G., Yandell, Mark, Kingsmore, Stephen F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515723/
https://www.ncbi.nlm.nih.gov/pubmed/34645491
http://dx.doi.org/10.1186/s13073-021-00965-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515723/
https://www.ncbi.nlm.nih.gov/pubmed/34645491
http://dx.doi.org/10.1186/s13073-021-00965-0

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