Unsupervised data-driven stratification of mentalizing heterogeneity in autism

Individuals affected by autism spectrum conditions (ASC) are considerably heterogeneous. Novel approaches are needed to parse this heterogeneity to enhance precision in clinical and translational research. Applying a clustering approach taken from genomics and systems biology on two large independen...

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Detalles Bibliográficos
Autores principales: Lombardo, Michael V., Lai, Meng-Chuan, Auyeung, Bonnie, Holt, Rosemary J., Allison, Carrie, Smith, Paula, Chakrabarti, Bhismadev, Ruigrok, Amber N. V., Suckling, John, Bullmore, Edward T., Ecker, Christine, Craig, Michael C., Murphy, Declan G. M., Happé, Francesca, Baron-Cohen, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5067562/
https://www.ncbi.nlm.nih.gov/pubmed/27752054
http://dx.doi.org/10.1038/srep35333

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5067562/
https://www.ncbi.nlm.nih.gov/pubmed/27752054
http://dx.doi.org/10.1038/srep35333

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