Predicting master transcription factors from pan-cancer expression data
Name
sciadv.abf6123.pdf
Description
Published version
Size
7.79 MB
Format
Adobe PDF
Checksum (MD5)
15daa6bc4a16b605f2192394ae6296e7
Author(s)
Young, Richard
Date Issued
2021
Journal
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Citation
Young, Richard. 2021. "Predicting master transcription factors from pan-cancer expression data." Science Advances, 7 (48).
Version
Final published version
Abstract
The CaCTS algorithm nominates cancer cell master transcription factors and guides a model of ovarian cancer regulatory circuitry.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1126/SCIADV.ABF6123
