Thesis Defense: Biomedical Data Sharing and Analysis at Scale

Speaker: Hyunghoon Cho , Berger Lab

Date: Wednesday, April 24, 2019

Time: 9:45 AM to 10:45 AM

Public: Yes

Location: 32-G575

Event Type: Thesis Defense

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Host: Bonnie Berger, Vinod Vaikuntanathan and Devavrat Shah

Contact: Patrice Macaluso, 617-253-3037,

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Reminder Subject: TALK: Biomedical Data Sharing and Analysis at Scale

Abstract: Researchers around the globe are gathering biomedical information at a massive scale. However, growing privacy concerns and computational overhead limit researchers' access to these data. In this talk, I will present novel computational methods that help overcome these barriers to improve the scalability of essential biomedical analysis pipelines. First, I will describe how modern cryptographic tools present a path toward broader data sharing and collaboration in biomedicine as demonstrated by my recent work on secure genome-wide association studies (GWAS) and pharmacological machine learning. For each domain, I will introduce our efficient privacy-preserving analysis protocol to achieve state-of-the-art accuracy while ensuring the input data remain private throughout the protocol. Our protocols newly achieve scalability to a million genomes or drug compounds by drawing on a set of techniques aimed at reducing redundancy in computation. Second, I will describe how the increasing redundancy in and structure of single-cell transcriptomic data can be leveraged to build a compact geometric sketch of the data, which can be used to accelerate and enhance the utility of downstream analysis. Our approach facilitates the sharing and analysis of emerging large-scale single-cell omics datasets including millions of cells. These results lay a foundation for more effective and collaborative biomedical research where individuals and institutes across nations share their data to enable novel life-saving discoveries.

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Created by Patrice Macaluso Email at Monday, April 22, 2019 at 3:23 PM.