Cargando…
Atlas of primary cell-type-specific sequence models of gene expression and variant effects
Human biology is rooted in highly specialized cell types programmed by a common genome, 98% of which is outside of genes. Genetic variation in the enormous noncoding space is linked to the majority of disease risk. To address the problem of linking these variants to expression changes in primary hum...
Autores principales: | Sokolova, Ksenia, Theesfeld, Chandra L., Wong, Aaron K., Zhang, Zijun, Dolinski, Kara, Troyanskaya, Olga G. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545936/ https://www.ncbi.nlm.nih.gov/pubmed/37703883 http://dx.doi.org/10.1016/j.crmeth.2023.100580 |
Ejemplares similares
-
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk
por: Zhou, Jian, et al.
Publicado: (2018) -
Discovery of biological networks from diverse functional genomic data
por: Myers, Chad L, et al.
Publicado: (2005) -
Implications of Big Data for cell biology
por: Dolinski, Kara, et al.
Publicado: (2015) -
Genome-wide landscape of RNA-binding protein target site dysregulation reveals a major impact on psychiatric disorder risk
por: Park, Christopher Y., et al.
Publicado: (2021) -
Modeling transcriptional regulation of model species with deep learning
por: Cofer, Evan M., et al.
Publicado: (2021)