Ernest Fraenkel

Ernest Fraenkel is a professor in MIT’s Department of Biological Engineering and a member of the Computer Science and Artificial Intelligence Laboratory and Broad Institute. His lab develops computational and experimental approaches to search for new therapeutic strategies for diseases. New experimental methods make it possible to measure cellular changes across the genome and proteome. They include genome-wide measurements of transcription, of protein-DNA interactions (ChIP-Seq), of genetic interactions, and of protein modifications. Each data source provides a narrow view of the cellular changes. However, by computationally integrating these data, the group can reconstruct signaling pathways and identify previously unrecognized regulatory mechanisms that help cause disease and may provide new approaches for treatment. Fraenkel was a postdoc at Harvard University and a Whitehead Fellow and Pfizer Computational Biology Fellow at the Whitehead Institute. He earned a BA in chemistry and physics from Harvard College, and a PhD in biology at MIT.

Publications

• Smith-Geater, C., Hernandez, S. J., Lim, R. G., Adam, M., Wu, J., Stocksdale, J. T., Wassie, B. T., Gold, M. P., Wang, K. Q., Miramontes, R., Kopan, L., Orellana, I., Joy, S., Kemp, P. J., Allen, N. D., Fraenkel, E., Thompson, L. M. (2020). Aberrant Development Corrected in Adult-Onset Huntington’s Disease iPSC-Derived Neuronal Cultures via WNT Signaling Modulation. Stem Cell Reports. Mar 10;14(3):406-419.
• Yildirim, F., Ng, C. W., Kappes, V., Ehrenberger, T., Rigby, S. K., Stivanello, V., Gipson, T. A., Soltis, A. R., Vanhoutte, P., Caboche, J., Housman, D. E., Fraenkel, E. (2019). Early epigenomic and transcriptional changes reveal Elk-1 transcription factor as a therapeutic target in Huntington’s disease. Proc Natl Acad Sci U S A. Dec 3;116(49):24840-24851.
• Archer, T. C., Ehrenberger, T., Mundt, F., Gold, M. P., Krug, K., Mah, C. K., Mahoney, E. L., Daniel, C. J., LeNail, A., Ramamoorthy, D., Mertins, P., Mani, D. R., Zhang, H., Gillette, M. A., Clauser, K., Noble, M., Tang, L. C., Pierre-François, J., Silterra, J., Jensen, J., Tamayo, P., Korshunov, A., Pfister, S. M., Kool, M., Northcott, P. A., Sears, R. C., Lipton, J. O., Carr, S. A., Mesirov, J. P., Pomeroy, S. L., Fraenkel, E. (2018). Proteomics, Post-translational Modifications, and Integrative Analyses Reveal Molecular Heterogeneity within Medulloblastoma Subgroups. Cancer Cell. Sep 10;34(3):396-410.e8.
• Pirhaji, L., Milani, P., Leidl, M., Curran, T., Avila-Pacheco, J., Clish, C. B., White, F. M., Saghatelian, A., Fraenkel, E. (2016). Revealing disease-associated pathways by network integration of untargeted metabolomics. Nat Methods. Sep;13(9):770-6.

Media

• March 11, 2019: MIT News, Using machine learning to improve subseasonal climate forecasting.
• September 14, 2018: MIT News, Protein analysis uncovers new medulloblastoma subtypes.
• July 5, 2016: MIT News, Mapping molecular neighborhoods.
• January 27, 2015: MIT News, Biology, driven by data.
• January 16, 2013: MIT News, Possible role for Huntington’s gene discovered.