A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

BACKGROUND: Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar disorder.With this aim, user-friendly, fully autom...

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Detalles Bibliográficos
Autores principales: Thomaidis, Georgios V., Papadimitriou, Konstantinos, Michos, Sotirios, Chartampilas, Evangelos, Tsamardinos, Ioannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668096/
https://www.ncbi.nlm.nih.gov/pubmed/38025660
http://dx.doi.org/10.1016/j.ibneur.2023.06.008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668096/
https://www.ncbi.nlm.nih.gov/pubmed/38025660
http://dx.doi.org/10.1016/j.ibneur.2023.06.008

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