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Link to the lab's
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Selected Publications
C Burdziak*, E Azizi*, S Prabhakaran, D Pe'er, A Nonparametric Multi-view model for Estimating Cell Type-Specific Gene Regulatory Networks, arXiv, 2019. (Equal Contribution) (pdf)
E Azizi*, AJ Carr*, G Plitas*, AE Cornish*, C Konopacki, S Prabhakaran, J Nainys, K Wu, V Kiseliovas, M Setty, K Choi, RM Fromme, P Dao, PT McKenney, RC Wasti, K Kadaveru, L Mazutis, AY Rudensky^, Dana Pe'er^, Single-cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment, Cell 174 (5): 1293-1308, 2018 (Featured as Cover Story) (outreach piece by NCI Cancer Systems Biology Consortium)
E Azizi*, S Prabhakaran*, A Carr, D Pe'er, Bayesian Inference for Single-cell Clustering and Imputing, Genomics and Computational Biology 3 (1), 46, 2017.
S Prabhakaran*, E Azizi*, A Carr, D Pe'er, Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data, Proceedings of The 33rd International Conference on Machine Learning (ICML), PMLR 48:1070-1079, 2016 (Acceptance rate: 24%) (pdf, supplementary, R code) (Recipient of Dataminr Poster Presentation Award, NYAS Machine Learning Symposium 2016).
* denotes equal contributions
^ denotes co-corresponding
E Azizi*, AJ Carr*, G Plitas*, AE Cornish*, C Konopacki, S Prabhakaran, J Nainys, K Wu, V Kiseliovas, M Setty, K Choi, RM Fromme, P Dao, PT McKenney, RC Wasti, K Kadaveru, L Mazutis, AY Rudensky^, Dana Pe'er^, Single-cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment, Cell 174 (5): 1293-1308, 2018 (Featured as Cover Story) (outreach piece by NCI Cancer Systems Biology Consortium)
E Azizi*, S Prabhakaran*, A Carr, D Pe'er, Bayesian Inference for Single-cell Clustering and Imputing, Genomics and Computational Biology 3 (1), 46, 2017.
S Prabhakaran*, E Azizi*, A Carr, D Pe'er, Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data, Proceedings of The 33rd International Conference on Machine Learning (ICML), PMLR 48:1070-1079, 2016 (Acceptance rate: 24%) (pdf, supplementary, R code) (Recipient of Dataminr Poster Presentation Award, NYAS Machine Learning Symposium 2016).
* denotes equal contributions
^ denotes co-corresponding
