The O'Connor lab develops statistical methods to analyze genetic association data and applies them to understand the genetic architecture and etiology of common disease. Particular areas of focus include the contribution of rare vs. common variants to...
Pranav Rajpurkar is driven by a fundamental passion for building reliable artificial intelligence (AI) technologies for biomedical decision making. His lab approaches biomedical problems with a computational lens, developing AI algorithms, datasets, and...
Research:
AI holds tremendous promise in enabling scientific breakthroughs and discoveries in diverse areas. Dr. Zitnik investigates machine learning with a current focus on networked systems that require infusing structure and domain knowledge. This...
Data generated by the rapidly advancing DNA sequencing technology provide the complete picture of population genetic variation and sequence divergence between species. We have been focused on the analysis of systematic re-sequencing datasets with the...
Mutational processes in cancer and normal cells; development of computational methods for genome and epigenome analysis.
We employ computational and statistical approaches to study various types of somatic mutations that arise in cancer cells and neurons...
Nils Gehlenborg received his PhD from the University of Cambridge and was a predoctoral fellow at the European Bioinformatics Institute (EMBL-EBI).
The goal of Gehlenborg's research is to improve human health by developing computational techniques and...
