Deciphering the genetic landscape of obesity: a data-driven approach to identifying plausible causal genes and therapeutic targets

OBJECTIVES: Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. However, identifying the causal genes, pathways, and tissues/cell types responsible for these associations remains a challenge, and standardized analysis workflows are lacking. Add...

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Detalles Bibliográficos
Autores principales: Ang, Mia Yang, Takeuchi, Fumihiko, Kato, Norihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10678330/
https://www.ncbi.nlm.nih.gov/pubmed/37620670
http://dx.doi.org/10.1038/s10038-023-01189-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10678330/
https://www.ncbi.nlm.nih.gov/pubmed/37620670
http://dx.doi.org/10.1038/s10038-023-01189-3

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