Papers: 10.1371/journal.pcbi.1004590
https://doi.org/10.1371/journal.pcbi.1004590
Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Models
Cited by: 20
Author(s): Dmitry Svetlichnyy, Hana Imrichová, Mark Fiers, Zeynep Kalender Atak, Stein Aerts
Published: almost 11 years ago
Software Mentions 2
Very Likely Science (100)
pypi: scikit-learn
A set of python modules for machine learning and data miningPapers that mentioned: 2,431
Very Likely Science (100)