Prof. Ernest Fraenkel

Professor of Biological Engineering
Associate Member, Broad Institute

Primary DLC

Department of Biological Engineering

MIT Room: 16-241

Areas of Interest and Expertise

Systems Biology
Transcriptional Regulation
Machine Learning
Biological Engineering
Computational Biology
Healthcare: Value-Based, Triple Aim, Future Models

Research Summary

The Fraenkel laboratory is developing 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. These technologies include genome-wide measurements of transcription, of protein-DNA interactions (ChIP-Seq), of genetic interactions, and of protein modifications. Each data source provides a very 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 contribute to the etiology of disease and may provide new approaches for treatment.

Current projects focus on the study of cancer, neurodegenerative diseases, and diabete

Recent Work

  • Video

    3.25.21-Health-Roundtable

    March 25, 2021Conference Video Duration: 89:1
    Manolis Kellis
    Professor, MIT Computer Science and Artificial Intelligence Lab
    Institute Member, Broad Institute of MIT and Harvard
    Ernest Fraenkel
    Professor, Biological Engineering
    Associate Member, Broad InstituteJuan Caicedo
    Schmidt Fellow, Broad Institute
    Caroline Uhler
    Associate Professor, Electrical Engineering and Computer Science and Institute for Data, Systems and Society
    Dipen Sangurdekar
    Head of Oncology Translational Genomics team, Takeda

    3.23.21-Health-Ernest-Fraenkel

    March 23, 2021Conference Video Duration: 14:46
    Ernest Fraenkel
    Professor, Biological Engineering
    Associate Member, Broad Institute

    AI in LIfe Science 2018 - Ernest Fraenkel

    December 4, 2018Conference Video Duration: 30:18

    The Roles of AI in Healthcare

    What are the prospects for applying AI to improve healthcare? Three types of problems that AI can address in healthcare will be outlined, the most challenging of which is the development of new therapeutics. To address this challenge, we leverage recent advances in machine learning and high-throughput experimentation to apply the engineering cycle to drug discovery. The engineering cycle is based on iteratively measuring a system, modeling it computationally, and manipulating it. Each time the cycle is completed, the results improve. This iterative approach is fundamental to all engineering design but, until now, has had limited impact on drug discovery. Progress on unpublished projects relating to these efforts will be described, including a collaborative, multi-institutional project called Answer ALS.

    2018 MIT AI in Life Sciences and Healthcare Conference

    Mapping Molecular Neighborhoods

    April 11, 2016MIT Faculty Feature Duration: 20:1

    Ernest Fraenkel
    MIT Associate Professor of Biological Engineering