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Patricia Goerner-Potvin
Patricia Goerner-Potvin
PhD Candidate, Department of Human Genetics, McGill University
Verified email at mail.mcgill.ca
Title
Cited by
Cited by
Year
Computational tools to unmask transposable elements
P Goerner-Potvin, G Bourque
Nature Reviews Genetics 19 (11), 688-704, 2018
2062018
Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning
TD Hocking, P Goerner-Potvin, A Morin, X Shao, T Pastinen, G Bourque
Bioinformatics 33 (4), 491-499, 2017
332017
Visual annotations and a supervised learning approach for evaluating and calibrating ChIP-seq peak detectors
TD Hocking, P Goerner-Potvin, A Morin, X Shao, G Bourque
arXiv preprint arXiv:1409.6209, 2014
22014
Supplementary materials for “Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning”
TD Hocking, P Goerner-Potvin, A Morin, X Shao, T Pastinen, G Bourque
2016
Visual annotations and a supervised learning approach for evaluating and calibrating ChIP-seq peak detectors
T Dylan Hocking, P Goerner-Potvin, A Morin, X Shao, G Bourque
arXiv e-prints, arXiv: 1409.6209, 2014
2014
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Articles 1–5