The Imielinski lab applies cancer genome assembly to study long range DNA structure in tumors. A key goal of the lab is to understand how complex somatic DNA rearrangements shape the tumor epigenome and drive cancer progression. More fundamentally, the lab is interested in using structural variation as a lens to study genomic plasticity and somatic evolution. The lab is committed to translating clinically relevant basic research findings into genomic diagnostics and incorporating these into precision cancer care.
+Marcin Imielinski, MD, PhD
Marcin Imielinski, MD, PhD, is a Core Member and Assistant Investigator at the New York Genome Center. He holds a joint appointment as Assistant Professor of Computational Genomics and Assistant Professor of Pathology and Laboratory Medicine at Weill Cornell Medicine, working directly with its Meyer Cancer Center and Englander Institute for Precision Medicine. Dr. Imielinski is also an Attending Molecular Pathologist at NewYork-Presbyterian Hospital.
Dr. Imielinski received a BS in Computer Science from Rutgers College in 2000. He obtained a PhD in genomics and computational biology and his MD from the University of Pennsylvania School of Medicine in 2008. He completed his residency in pathology at the Massachusetts General Hospital in 2011, and a fellowship in molecular genetic pathology at Harvard Medical School in 2012. Prior to joining NYGC, he was a postdoctoral fellow in computational cancer genomics at the Broad Institute of Harvard and MIT, under the mentorship of Drs. Matthew Meyerson and Gad Getz.
Dr. Imielinski is a board-certified molecular genetic pathologist. His research includes more than 40 peer-reviewed publications across several areas of genomics and computational biology. He is a recipient of a Burroughs Wellcome Career Award for Medical Scientists.
Dr. Imielinski’s research interests are to apply high-throughput sequencing and computation to study patterns of somatic genomic variation in cancer. He is specifically interested in probing long-range cancer genome structure through the use of cutting-edge sequencing protocols and the development of novel machine learning and data visualization approaches. Dr. Imielinski is committed to expanding the role of computation and data science in laboratory medicine, and envisions a future in which “quantitative pathologists” help direct treatment choices through the application of statistical intuition and sophisticated multivariate analyses.
Marcin Imielinski, Guangwu Guo, Matthew MeyersonInsertions and Deletions Target Lineage-Defining Genes in Human Cancers.
Cell. 2017 Jan 11. PMID: 28089356