07/10/2017 @ 13:30-14:15
Research Talk by Jennifer Listgarten
Machine learning for CRISPR gene editing 
1. Fusi, N., Smith, I., Doench, J. and Listgarten, J., 2015. In silico predictive modeling of CRISPR/Cas9 guide efficiency. bioRxiv, p.021568.
2. Listgarten, J., Weinstein, M., Elibol, M., Hoang, L., Doench, J. and Fusi, N., 2016. Predicting off-target effects for end-to-end CRISPR guide design. bioRxiv, p.078253.
3. Doench, J.G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E.W., Donovan, K.F., Smith, I., Tothova, Z., Wilen, C., Orchard, R. and Virgin, H.W., 2016. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nature biotechnology.
Jennifer Listgarten | Machine learning for CRISPR gene editing | CGSI 2017