Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers

Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers

Epigenomic data on chromatin accessibility and transcription factor occupancy can reveal enhancer landscapes in cancer. Here, the authors develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to model the impact of enhancers on transcriptional...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Hatice U. Osmanbeyoglu, Fumiko Shimizu, Angela Rynne-Vidal, Direna Alonso-Curbelo, Hsuan-An Chen, Hannah Y. Wen, Tsz-Lun Yeung, Petar Jelinic, Pedram Razavi, Scott W. Lowe, Samuel C. Mok, Gabriela Chiosis, Douglas A. Levine, Christina S. Leslie
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
Materias:
Science
Q
Acceso en línea:https://doaj.org/article/ae04ca5ec19545a0b464c26486748931
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Epigenomic data on chromatin accessibility and transcription factor occupancy can reveal enhancer landscapes in cancer. Here, the authors develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to model the impact of enhancers on transcriptional programs in gynecologic and basal breast cancers.

Ejemplares similares