Portfolio category: CGSI 2017

Can Alkan | Next-generation sequence characterization of complex genome structural variation | CGSI 2017

07/11/2017 @ 12:00-12:45 Research Talk by Can Alkan Next-generation sequence characterization of complex genome structural variation 1. Alkan, C., Coe, B.P. and Eichler, E.E., 2011. Genome structural variation discovery and genotyping. Nature Reviews Genetics, 12(5), pp.363-376. 2. Alkan, C., Kidd, J.M., Marques-Bonet, T., Aksay, G., Antonacci, F., Hormozdiari, F., Kitzman, J.O., Baker, C., Malig, M.,…

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James Zou | Deep learning in genomics | Introduction and examples | CGSI 2017

07/11/2017 @ 11:15-12:00 Research Talk by James Zou Deep learning in genomics: Introduction and examples

William (Xiaoquan) Wen | Bayesian approaches for integrative genetic association analysis | Data integration and scalable computation | CGSI 2017

07/11/2017 @ 10:00-10:45 Research Talk by William (Xiaoquan) Wen Bayesian approaches for integrative genetic association analysis: Data integration and scalable computation 1. Wen, X., Lee, Y., Luca, F. and Pique-Regi, R., 2016. Efficient integrative multi-SNP association analysis via Deterministic Approximation of Posteriors. The American Journal of Human Genetics, 98(6), pp.1114-1129. 2. Wen, X., Pique-Regi, R….

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Lior Pachter | An introduction to pseudoalignment | CGSI 2017

07/10/2017 @ 09:15-10:00 Research Talk by Lior Pachter An introduction to pseudoalignment 1. Bray, N.L., Pimentel, H., Melsted, P. and Pachter, L., 2016. Near-optimal probabilistic RNA-seq quantification. Nature biotechnology, 34(5), pp.525-527.

Dana Pe’er | Imputation in Single Cell RNA-seq Data | CGSI 2017

07/10/2017 @ 14:45-15:30 Research Talk by Dana Pe’er Imputation in Single Cell RNA-seq Data 1. van Dijk, D., Nainys, J., Sharma, R., Kathail, P., Carr, A.J., Moon, K.R., Mazutis, L., Wolf, G., Krishnaswamy, S. and Pe’er, D., 2017. MAGIC: A diffusion-based imputation method reveals gene-gene interactions in single-cell RNA-sequencing data. bioRxiv, p.111591. 2. Prabhakaran, S.,…

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Jennifer Listgarten | Machine learning for CRISPR gene editing | CGSI 2017

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…

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