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Bonnie Berger, Ph.D.

AIMBE College of Fellows Class of 2016
For outstanding research contributions to computational biology and mentoring of future bioinformatics leaders

Cryptographic protocol enables greater collaboration in drug discovery

Via MIT | October 18, 2018

MIT researchers have developed a cryptographic system that could help neural networks identify promising drug candidates in massive pharmacological datasets, while keeping the data private. Secure computation done at such a massive scale could enable broad pooling of sensitive pharmacological data for predictive drug discovery.

Datasets of drug-target interactions (DTI), which show whether candidate compounds act on target proteins, are critical in helping researchers develop new medications. Models can be trained to crunch datasets of known DTIs and then, using that information, find novel drug candidates.

In recent years, pharmaceutical firms, universities, and other entities have become open to pooling pharmacological data into larger databases that can greatly improve training of these models. Due to intellectual property matters and other privacy concerns, however, these datasets remain limited in scope. Cryptography methods to secure the data are so computationally intensive they don’t scale well to datasets beyond, say, tens of thousands of DTIs, which is relatively small… Continue reading.

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Protecting confidentiality in genomic studies

Via MIT | May 7, 2018

Genome-wide association studies, which look for links between particular genetic variants and incidence of disease, are the basis of much modern biomedical research.

But databases of genomic information pose privacy risks. From people’s raw genomic data, it may be possible to infer their surnames and perhaps even the shapes of their faces. Many people are reluctant to contribute their genomic data to biomedical research projects, and an organization hosting a large repository of genomic data might conduct a months-long review before deciding whether to grant a researcher’s request for access.

In a paper appearing today in Nature Biotechnology, researchers from MIT and Stanford University present a new system for protecting the privacy of people who contribute their genomic data to large-scale biomedical studies. Where earlier cryptographic methods were so computationally intensive that they became prohibitively time consuming for more than a few thousand genomes, the new system promises efficient privacy protection for studies conducted over as many as a million genomes.

“As biomedical researchers, we’re frustrated by the lack of data and by the access-controlled repositories,” says Bonnie Berger, the Simons Professor of Mathematics at MIT and corresponding author on the paper… Continue reading.

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Bonnie Berger, Ph.D. To be Inducted into Medical and Biological Engineering Elite

Via AIMBE | March 1, 2016

WASHINGTON, D.C.— The American Institute for Medical and Biological Engineering (AIMBE) has announced the pending induction of Bonnie Berger, Ph.D., Professor of Applied Math and Computer Science at MIT, and head of the Computation and Biology group, , Massachusetts Institute of Technology, to its College of Fellows. Dr. Berger was nominated, reviewed, and elected by peers and members of the College of Fellows For outstanding research contributions to computational biology and mentoring of future bioinformatics leaders.

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