Aaron Newman

Dr Aaron Newman completed his Ph.D. at the University of California, Santa Barbara, through the Biomolecular Science and Engineering Program. He is the Assitant Professor at Standford University in the department of Biomedical Data Science. The Newman Group combines computational and experimental techniques to study the cellular organization of complex tissues, with a focus on determining the phenotypic diversity and clinical significance of tumor cell subsets. The group is interested in developing innovative data science tools that illuminate the cellular hierarchies and stromal elements that underlie tumor initiation, progression, and response to therapy. As part of this focus, they develop new algorithms to resolve cellular states and multicellular communities, tumor developmental hierarchies, and single-cell spatial relationships from genomic profiles of clinical biospecimens. The key findings are explored experimentally with the goal of translating promising findings into the clinic. The latest software available from Newman’s group is CytoTRACE, a simple however robust computational framework that predicts a cell’s differenciating states from single-cell RNA sequencing data (Gulati et al., 2020). Other software outcomes can be found on the lab’s website.

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Newman Lab at Standford University

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Bioinformatics and Computational Biology 0 Digital Cytometry 0 Cancer Prognostic Tools 0 Machine Learning Based Cell Profiling 0 Next Generation Seuquencing 0

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  1. Gulati GS, Sikandar SS, Wesche DJ, et al. Single-cell transcriptional diversity is a hallmark of developmental potential. Science. 2020;367(6476):405-411. doi:10.1126/science.aax0249

  2. Newman AM, Steen CB, Liu CL, et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat Biotechnol. 2019;37(7):773-782. doi:10.1038/s41587-019-0114-2

  3. Newman AM, Lovejoy AF, Klass DM, et al. Integrated digital error suppression for improved detection of circulating tumor DNA. Nat Biotechnol. 2016;34(5):547-555. doi:10.1038/nbt.3520

  4. Gentles AJ, Newman AM, Liu CL, et al. The prognostic landscape of genes and infiltrating immune cells across human cancers. Nat Med. 2015;21(8):938-945. doi:10.1038/nm.3909

  5. Newman AM, Liu CL, Green MR, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453-457. doi:10.1038/nmeth.3337


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