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Topological gene expression networks recapitulate brain anatomy and function

Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key result...

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Detalles Bibliográficos
Autores principales: Patania, Alice, Selvaggi, Pierluigi, Veronese, Mattia, Dipasquale, Ottavia, Expert, Paul, Petri, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6663211/
https://www.ncbi.nlm.nih.gov/pubmed/31410377
http://dx.doi.org/10.1162/netn_a_00094
Descripción
Sumario:Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene set and find that co-expression networks produced by Mapper return a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that network based descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenges.