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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
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 |
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