Noah Friedman Email & Phone Number

Jackson, Wy, Us

New York, Ny, Us

Bethesda, Md, Us

Leading a team developing AI tools, strategy and policy for ARPA-H.

Austin, Texas, Us

Austin, Texas, Us

New York, Ny, Us

• Responsible for development of pipeline for copy number informed detection of tumor material in circulating tumor DNA. Oversaw development from initial proof of concept to performance validation to integration into product pipeline• Implemented algorithm to characterized and detect tumor signal as determined by genomic features including allele specific copy number, tumor clonality, mutation copy number and somatic mutations• Developed algorithms for robust, replicable and fast performance in cloud environment: scripting, automated evaluation, high performance computing (aws) configuration• Prepared reports and led research initiatives to tailor product to integrate signal across various tumor derived signal classes, and characterized the difference in these analytes between tumor and normal data• Examined and fine-tuned algorithm performance across a diverse set of cancers representing distinct cancer types, genomic profiles and cancer tumor fractions• Used liquid biopsy data to track and categorize the evolution of tumors over treatment course without the need for a tissue biopsy

New York, Ny, Us

• First author publication drafted on evolutionary consequences of hypermutation in human cancer: disambiguating driver and passenger mutations, understanding positive and negative selection in hypermutated cancer, understanding temporal development of hypermutated cancer, developing a framework to understand evolutionary imperatives of hypermutated cancer• Genomics research on evolution of cancer centered around analysis of targeted sequence cohort of 50k patients• Analyses of the contribution of environmental and endogenous mutational processes to cancer development through mutational signatures, copy number changes, phylogenetic analysis• Analyses of intra-tumoral heterogeneity, mechanisms of gene inactivation, disambiguation of cancer driver and passenger mutations, mutational event validations, copy number changes in human cancer and selective landscape of human malignancies• Contributions to published papers on BRCA dysfunction in human cancer, comparisons between exome and targeted panel sequencing, compound mutagenesis in cancer, landscape of microsatellite instability in human cancer• Extensive work with cancer data pipelines, analytical methods and visualization for publication quality figures

Stanford, Ca, Us

• Redesigned and augmented ‘Sequence to medical phenotype,’ an algorithmic pipeline that filters and annotates raw genetic data with based on variant pathogenicity, frequency, and other measureso Changed pipeline runtime design to facilitate debugging and modular additionso Implemented new filtering and analytical components based on family geneticso Used cloud API to implement automatic execution of analysis pipeline• Created an interactive website hosting a visualization of genomic data for use by the genetic counseling team and collaborators• Trained a deep learning model to distinguish real and artifact sequencing data based on images from the Integrative Genomics Viewer (IGV)

Master Of Science - Ms, Biomedical Informatics

Bachelor Of Science - Bs, Symbolic Systems