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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Nature Singapore
2023
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| Materias: | |
| 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 |