Litvin, Oren

Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis

Levine, J. H., Simonds, E. F., Bendall, S. C., Davis, K. L., Amir, E.-A. D., Tadmor, M. D., Litvin, O., Fienberg, H. G., Jager, A., Zunder, E. R., et al. (2015) · Cell

Acute Myeloid Leukemia ResearchSingle-cell and spatial transcriptomics

Cited by 2,303

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

An integrated approach to uncover drivers of cancer

Akavia, U. D., Litvin, O., Kim, J., Sanchez-Garcia, F., Kotliar, D., Causton, H. C., Pochanard, P., Mozes, E., Garraway, L. A., & Pe'er, D. (2010) · Cell

Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer

Cited by 484

High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis

Patwardhan, R. P., Lee, C., Litvin, O., Young, D. L., Pe'er, D., & Shendure, J. (2009) · Nature Biotechnology

Genomics and Chromatin DynamicsGene Regulatory Network Analysis

Cited by 377

Conditional density-based analysis of T cell signaling in single-cell data

Krishnaswamy, S., Spitzer, M. H., Mingueneau, M., Bendall, S. C., Litvin, O., Stone, E., Pe’er, D., & Nolan, G. P. (2014) · Science

Gene Regulatory Network AnalysisSingle-cell and spatial transcriptomics

Cited by 225