bioRxiv preprint doi: https://doi.org/10.1101/631895; this version posted May 8, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Machine learning-based identification and cellular validation of Tropomyosin 1 as a genetic inhibitor of hematopoiesis. Thom CS1,2,3*, Jobaliya CD4,5, Lorenz K2,3, Maguire JA4,5, Gagne A4,5, Gadue P4,5, French DL4,5, Voight BF2,3,6* 1Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA 2Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 3Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 4Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, PA, USA 5Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA 6Institute of Translational Medicine and Therapeutics, University of Pennsylvania, PA, USA *Corresponding authors:
[email protected],
[email protected] bioRxiv preprint doi: https://doi.org/10.1101/631895; this version posted May 8, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Introductory paragraph A better understanding of the genetic mechanisms regulating hematopoiesis are necessary, and could augment translational efforts to generate red blood cells (RBCs) and/or platelets in vitro.