William KM Lai

The primary focus of my research program is to understand how protein-complexes target the genome, how protein binding changes across cell states, and how mis-regulation of these interactions can result in disease-phenotypes. My group combines novel genomic assays with custom bioinformatic software development. We pursue ‘big-data’ projects that generate thousands of unique (epi)genomic datasets across human, mouse, and yeast model systems.

As the Director of the Cornell EpiGenomics Core facility, my group works hand-in-hand with physician scientists at Cornell Weill medical campus to apply our epigenomic technology and algorithmic approaches to biomedical specimens to investigate the fundamental nature of human diseases. Combining wet-bench biochemical genomic technology with analytical bioinformatic algorithmic approaches allows us to understand the fundamental rules of protein-DNA interactions and how these rules are broken in diseased patient samples.

The volume and dimensionality of our data typically requires application of machine learning approaches as well as eXplainable AI algorithms. To support our analysis, we heavily leverage NSF-provided ACCESS resources. Our students are trained to perform advanced informatic analysis across a wide spectrum of heterogeneous and high-performance compute systems.

The growing complexity of STEM research now frequently demands expertise in more domains of science than what any single research group is able to encompass. As the Director of the Cornell Center for Vertebrate Genomics, my mandate is to identify, develop, and support cross-discipline collaborations and foster an engaged community across the University. In a world that increasingly requires collaboration to leverage the latest and most powerful technolgoies, it is my priviledge to support the researchers in the Center.

The greatest biological discoveries are achieved when we can pair multiple distinct approaches (e.g., biochemistry, molecular biology, bioinformatics, etc.) to build something greater than the sum of its parts.