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BIBTEX RIS

Predicting master transcription factors from pan-cancer expression data

2021; American Association for the Advancement of Science; Volume: 7; Issue: 48 Linguagem: Inglês

10.1126/sciadv.abf6123

ISSN

2375-2548

Autores

Jessica Reddy, Marcos A. Fonseca, Rosario I. Corona, Robbin Nameki, Felipe Segato Dezem, Isaac A. Klein, Heidi Chang, Daniele Chaves‐Moreira, Lena K. Afeyan, Tathiane M. Malta, Xianzhi Lin, Forough Abbasi, Alba Font‐Tello, Thaís S. Sabedot, Paloma Cejas, Norma I. Rodríguez-Malavé, Ji-Heui Seo, De‐Chen Lin, Ursula A. Matulonis, Beth Y. Karlan, Simon A. Gayther, Bogdan Paşaniuc, Alexander Gusev, Houtan Noushmehr, Henry W. Long, Matthew L. Freedman, Ronny Drapkin, Richard A. Young, Brian J. Abraham, Kate Lawrenson,

Tópico(s)

Epigenetics and DNA Methylation

Resumo

The CaCTS algorithm nominates cancer cell master transcription factors and guides a model of ovarian cancer regulatory circuitry.

Referência(s)