@article{fusi2016predicting,
author = {Fusi, Nicolo and Listgarten, Jennifer and Elibol, Melih and Doench, John and Weinstein, Michael and Hoang, Luong},
title = {Predicting off-target effects for end-to-end CRISPR guide design},
year = {2016},
month = {October},
abstract = {To enable more effective guide design we have developed the first machine learning-based approach to assess CRISPR/Cas9 off-target effects. Our approach consistently and substantially outperformed the state-of the-art over multiple, independent data sets, yielding up to a 6-fold improvement in accuracy. Because of the large computational demands of the task, we also developed a cloud-based service for end-to-end guide design which incorporates our previously reported on-target model, Azimuth, as well as our new off-target model, Elevation (http://approjects.co.za/?big=en-us/research/project/crispr)},
publisher = {biorxiv},
url = {http://approjects.co.za/?big=en-us/research/publication/predicting-off-target-effects-end-end-crispr-guide-design/},
}