Published in
American Association for the Advancement of Science, Science Advances, 48(7), 2021
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Predicting master transcription factors from pan-cancer expression data
Journal article published in 2021 by
Jessica Reddy 
,
Marcos A. S. 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 ,
Thais Sabedot ,
Paloma Cejas
and other authors.
,
Marcos A. S. 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 ,
Thais Sabedot ,
Paloma Cejas
and other authors.
This paper is made freely available by the publisher.
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Abstract
The CaCTS algorithm nominates cancer cell master transcription factors and guides a model of ovarian cancer regulatory circuitry.