John Vivian

Background

About John Vivian

Applying computational expertise to generate insights into the immune responses of oncology patients from one of the world’s largest database of precise, comprehensive antibody and T cell receptor repertoires. Performing analyses on hundreds of millions of antibody sequences, writing scalable bioinformatics pipelines in Python/Nextflow, and developing methods for assays. Bioinformatics PhD from UC Santa Cruz under David Haussler and Benedict Paten in the Computational Genomics Lab at the Genomics Institute. I spent the first two years helping develop Toil, an open-source distributed workflow system designed for massive scalability. This work enabled a large-scale compute of gene- and isoform-level expression values from RNA-seq samples across several important datasets using a Toil-based RNA-seq package I developed and maintain. My thesis work also included the development of a Bayesian framework for detecting gene expression outliers in individual samples to improve drug candidate selection. & hl=en