Data-driven understanding of human disease: from machine learning methods to biological discoveries
Olga Troyanskaya (Princeton University)
Distinguished Lecture Series
Thursday, December 6, 2018, 3:30 pm
EEB-105
Abstract
How does the same DNA sequence lead to such different cells in the brain versus the lungs? What genomic signals encode our predisposition to Parkinson's disease? Why and how do scientists use worms to study human disease? I will discuss these questions with a focus on development and application of machine learning methods, including deep learning, Bayesian, and semi-supervised approaches, for biomedical data.
More specifically, I will address a key challenge in biomedical science -- development of a complete understanding of the genomic architecture of disease. Yet the increasingly wide availability of genomic data (including whole genome sequencing and expression) has far outpaced our ability to analyze these datasets. Challenges include interpreting the 98% of the genome that is noncoding (sometimes referred to as 'junk' DNA), detangling genomic signals regulating tissue-specific gene expression, mapping the resulting genetic circuits in disease-relevant cell types, and, finally, integrating the vast body of biological knowledge from model organisms with observations in humans. In my seminar, I will discuss methods that we have developed to address these challenges, and present their applications to autism, Parkinson's, and cardiovascular disease.
Bio
Olga Troyanskaya is a Professor in the Lewis-Sigler Institute for Integrative Genomics and the Department of Computer Science at Princeton University. Her work bridges computer science and molecular biology in an effort to develop better methods for analysis of diverse genomic data with the goal of understanding and modeling protein function and interactions in biological pathways. Her group includes computational and experimental aspects and tackles diverse questions including developing integrative technologies for pathway prediction and the study of biological networks in complex human disease. Dr. Troyanskaya received her Ph.D. from Stanford University and is a recipient of the Sloan Research Fellowship, the NSF CAREER award, the Howard Wentz faculty award, and the Blavatnik Finalist Award. She has also been honored with the Ira Herskowitz Award from The Genetics Society of America and is the 2011 recipient of the Overton Prize in computational biology.