Broad Institute Next Generation in Biomedicine Symposium

November 5, 2018
8:30 a.m. - 5:30 p.m.
Broad Institute Auditorium, 415 Main Street, Cambridge, MA

 

Pre-register to attend: https://nextgenbiomedicine2018.eventbrite.com

Questions? Contact juniorsymposium@broadinstitute.org

 

2018 Symposium Presenters

Noemi Andor
Instructor, Stanford University
A pharmacodynamic model of a clone’s DNA-damage therapy sensitivity using single cell genomics

Elham Azizi
Dana Pe'er Lab at Memorial Sloan Kettering Cancer Center
Bayesian hierarchical modeling of immune phenotypes in the breast tumor microenvironment

David Booth
Nicole King lab, University of California at Berkeley
Building a simple model of animal multicellularity

Jonas Demeulemeester
Peter Van Loo lab, The Francis Crick Institute 
Clustered mutational processes in cancer

Fangyuan Ding
Michael Elowitz lab, California Institute of Technology
Quantitative single cell splicing analysis reveals an 'economy of scale' filter for gene expression

Gozde Durmus
Burroughs Wellcome Fund CASI Fellow, Ronald Davis lab & Lars Steinmetz lab, Stanford University
Levitating rare biological materials to decode the fundamentals

Karuna Ganesh
Assistant Attending Physician, Memorial Sloan Kettering Cancer Center
Instructor, Weill Cornell Medical College
Regenerative origin of metastasis stem cells

Xiaojing Gao
Michael Elowitz lab, California Institute of Technology
Programmable protein circuits in mammalian cells

Yury Goltsev
Gary Nolan lab, Stanford University
Dissection of cellular niches by multi-dimensional tissue imaging

Britney Johnson
Craig Cameron lab, Washington University School Of Medicine
Self vs. Non-Self: Mechanism of RNA recognition by IFIT proteins

Leeat Keren
Michael Angelo lab, Stanford University
Unravelling the geography of the tumor immune microenvironment using multiplexed imaging

Silvana Konermann
Hanna H. Gray Fellow, Salk Institute
Manipulating mammalian transcription for the interrogation of Alzheimer’s disease

Jianzhu Ma
Trey Ideker Lab, University of California San Diego 
Interpretable machine learning for cancer study

Calin Plesa
Sri Kosuri lab, University of California Los Angeles
Multiplexed engineering and characterization of protein families using DropSynth

Melissa Reeves
UCSF Sandler Fellow
Tumor heterogeneity & its impact on the immune response

Nikolay Samusik
Gary Nolan lab, Stanford University
Architecture of tumor-immune interactions revealed by CODEX multidimensional imaging

Wesley Tansey
Raul Rabadan lab, Columbia University
Dose-response modeling in high throughput cancer drug screening: probabilistic deep learning with statistical guarantees

Samra Turajlic
Cancer Research UK Clinician Scientist, The Francis Crick Institute 
Tracking renal cancer evolution

Fabio Zanini
Stephen Quake lab, Stanford University
Virus-inclusive single cell RNA-Seq elucidates pathogen-host interactions during dengue virus infection

Marinka Zitnik
Jure Leskovec lab, Stanford University
New machine learning for biomedical sciences