Biomedical Data Science Day in Detail

Please don't forget to register if you have not yet done so. Thank you!

 New Frontiers in Biomedical Data Science

AGENDA

8:00 Registration and breakfast

8:30 Welcome, Today’s Agenda, Thoughts on the Intersection of Biomedical Research and Data Science

  • Emily CarterPrinceton University. Dean, School of Engineering and Applied Science. Gerhard R. Andlinger Professor in Energy and the Environment. Professor of Mechanical and Aerospace Engineering and Applied and Computational Mathematics.
     
  • Robert HuginCelgene. Executive Chairman.
     
  • Jennifer RexfordPrinceton University. Gordon Y.S. Wu Professor in Engineering. Professor of Computer Science. Chair, Department of Computer Science.
     
  • Leslie Greengard, Flatiron Institute/Simons Foundation, Center for Computational Biology. Director, Center for Computational Biology.
     
  • Nicolo FusiMicrosoft Research. Research Scientist.

10:00 Break
 

10:15 Faculty Research Briefs, Part I

  • "Computational Cancer Genomics." 
    Ben Raphael
    Princeton University. Professor of Computer Science. 

Cancer is a complex disease with extensive mutational heterogeneity within and across patients.  We will highlight computational approaches we have developed to analyze interacting networks of mutations across cancer patients and to study tumor evolution within patients.
 

  • "Data-driven understanding of human disease." 
    Olga G. Troyanskaya
    , Princeton University. Professor of Computer Science and the Lewis-Sigler Institute for Integrative Genomics. 

We developed a deep learning-based algorithmic framework to predict the effect of mutations in genomic sequence without any prior information and use these predictions to accurately prioritize disease-associated sequence variants. On the cellular and organismal level, integrated analysis of big data in functional genomics is leveraged to study tissue-lineage-specific protein function and interactions and to identify genes involved in disease in a novel approach for re-prioritizing quantitative genetics studies results. This includes applications to cardiovascular disease, neurodegenerative disorders and autism.

 

  • "'Interaction-based discovery of cancer genes.'" 
    Mona Singh,
     Princeton University. Professor of Computer Science and the Lewis Sigler Institute for Integrative Genomics.

A central goal in cancer genomics is to identify the somatic alterations that underpin tumor initiation and progression. We introduce a method to identify genes whose interaction interfaces are enriched in somatic mutations, a pattern commonly observed across many known cancer driver genes.   Our method recapitulates known cancer driver genes, and discovers novel, relatively rarely-mutated genes with likely roles in cancer.

  • “Quantitating Quality of Life: How long-lived mutants maintain function with age”
    Coleen Murphy, Princeton University. Professor of Molecular Biology and the Lewis-Sigler Institute for Integrative Genomics.

My lab studies the regulation of longevity and age-related declines, such as loss of cognitive and reproductive functions with age, using the nematode C. elegans and human cells. We have developed microfluidic assays to study timing of reproduction during reproductive aging, the strength of the animal’s outer cuticle, and various tests of neuronal behaviors, together with gene expression changes that are regulated in a tissue-specific manner. This information can help explain how long-lived animals are able to carry out functions for an extended time, and may help shed light on how to extend analogous functions in humans.

12:15 Lunch
 

1:45 Faculty Research Briefs , Part II

  • "Understanding the Human Brain: A Reverse Engineering Challenge of Truly Cosmic Proportions."
    Jonathan D. Cohen
    , Princeton University. Robert Bendheim and Lynn Bendheim Thoman Professor in Neuroscience. Professor of Psychology and the Princeton Neuroscience Institute. Co-Director, Princeton Neuroscience Institute. 

Understanding how the human brain gives rise to mental function is one of the greatest challenges science has faced, given the scale and complexity of the computations the brain carries out.  Our Institute combines imaging of brain function (from single neurons to whole brain activity) with modern methods from statistics and machine learning to measure, analyze, and simulate those computations, in an effort to better understand them.  Progress is leading not only to deeper insight into human brain function, but also how to emulate its remarkable abilities in artificial systems.

  • "Mapping the connectome with deep learning and crowdsourcing." 
    H. Sebastian Seung,
     Princeton University. Evnin Professor in Neuroscience. Professor of Computer Science and the Princeton Neuroscience Institute. Co-Director, Program in Neuroscience.

The Seung Lab uses techniques from deep learning and social computing to extract brain structure from light and electron microscopic images.  EyeWire showcases our approach by mobilizing gamers from around the world to create 3D reconstructions of neurons by interacting with a deep convolutional network.

  • "From available patient data to transforming hospitals: Machine learning for personalized healthcare."
    Barbara Engelhardt, Princeton University. Assistant Professor of Computer Science.

My group studies and analyzes genomics and biomedical data through the development of machine learning and statistical methodologies. This talk will describe recent work from my group on models for the joint analysis of histopathological images and high-dimensional genomics data.

 3:15 Break

3:30 Panel: Building critical mass for biomedical data science in the NY/NJ/PA corridor

  • Robert Hugin, Celgene. Executive Chairman.
     
  • Jen Rexford, Princeton University. Gordon Y.S. Wu Professor in Engineering. Professor of Computer Science. Chair, Department of Computer Science.
     
  • Leslie Greengard, Flatiron Institute/Simons Foundation, Center for Computational Biology. Director, Center for Computational Biology.
     
  • Debbie Hart, BioNJ, President & CEO. 
     
  • William J. Welsh, Rutgers, the State University of New Jersey. Norman H. Edelman Professor in Bioinformatics, Department of Pharmacology, Robert Wood Johnson Medical School. Associate Director, Division of Cheminformatics, Biomedical Informatics Shared Resource, Rutgers-Cancer Institute of New Jersey (RCINJ)
     
  • Elizabeth J. BruceMicrosoft Research. University Lead.
     
  • Prakash Balan, National Science Foundation. Program Director, IUCRC.
     
  • Plus, other invited industry and government leaders.

5:00 Cocktail Reception 

Logistics for the Day

 

Location

The event will be held in the Convocation Room at the Friend Center.

The Friend Center address is 65 Olden Street, Princeton, NJ 08540; it is at the corner of Olden and William Streets.  Directions to the Friend Center are found here.

There will be signs directing you to the building. 

Parking

Before 9:00 am, we recommend parking in the metered street parking on Williams Street, Olden Street, and Prospect Avenue, as shown. We are happy to pay for your on-street parking. On Tuesday, October 24, we will send registered attendees a final email on logistics with additional information.

If you arrive after 9:00 am, street parking may be extremely limited. If you cannot find metered street parking, we recommend parking further east on Prospect Avenue (past Fitzrandolph Rd), or in University Lot 21, located at the intersection of Faculty Rd and Fitzrandolph Rd in Princeton, approximately .7 miles away.

Breakfast, Lunch and Cocktail Reception

A continental breakfast and full lunch will be provided. If you have any special dietary needs, please reach out to Spencer Reynolds at spencerr@princeton.edu.

We also hope you will stay and join us for a reception immediately after the event.

Special Accommodations

If you are in need of any special accommodations for accessibility, please contact Spencer Reynolds at spencerr@princeton.edu.

Media and Social Media

This event will be photographed and video recorded.

If you are so inclined, please feel free to share this event on social media during and after the event. The event hashtag is:  #PrincetonBioData

Thanks so much! We're looking forward to seeing everyone!