Our Collaborations

Brian D. Piening, PhD, Providence Health

Brian D. Piening, PhD, Providence Health

Dr. Piening is trained in genetics, genomics and bioinformatics. Along with leading the Cancer Immuno-Genomics Lab at the Earle A. Chiles Research Institute, a Providence Center of Excellence for immuno-oncology and cellular therapy, he also serves as program director of Providence Genomics. There, he uses comprehensive genomic profiling to develop personalized treatment plans for people with advanced cancer. The laboratory is one of only a handful in the world that performs whole genome sequencing in a clinical context and is the dedicated clinical sequencing facility for Providence.

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Mike Snyder, PhD, Stanford Medicine

Mike Snyder, PhD, Stanford Medicine

Snyder Lab was the first to perform a large-scale functional genomics project in any organism, and has developed many technologies in genomics and proteomics. These including the development of proteome chips, high resolution tiling arrays for the entire human genome, methods for global mapping of transcription factor binding sites (ChIP-chip now replaced by ChIP-seq), paired end sequencing for mapping of structural variation in eukaryotes, de novo genome sequencing of genomes using high throughput technologies and RNA-Seq. These technologies have been used for characterizing genomes, proteomes and regulatory networks.

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Jessica van Setten

Jessica van Setten

Jessica specializes in the complex genetics of cardiovascular diseases and traits, specifically cardiomyopathies, heart failure, heart transplantation, and ECG. She is leading multiple projects, supervising and mentoring multiple PhDs, PostDocs, and (under)graduate students.

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iGeneTRAiN

iGeneTRAiN

iGeneTRAiN aims to coordinate genetic and other patient biospecimen and clinical datasets, from sites across the world engaged in clinical and research transplant programs. We are well underway in generating massive, integrated datasets that will empower us to identify factors associated with transplant success. Relevant information includes data from clinical, genetic, protein, metabolite, and a range of other studies, including wearable devices.

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