A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets.

Background: Medical digital twins are computational disease models for drug discovery and treatment. Unresolved problems include how to organize and prioritize between disease-associated changes in digital twins, on cellulome- and genome-wide scales. We present a dynamic framework that can be used to model such changes and thereby prioritize upstream regulators (URs) for biomarker- and drug discovery.

Generation of CD34 Fluorescent Reporter Human Induced Pluripotent Stem Cells for Monitoring Hematopoietic Differentiation.

Hematopoietic stem and progenitor cells (HSPCs) derived from human induced pluripotent stem cells (hiPSCs) hold great promise for disease modeling, drug screens, and eventually cell therapy approaches. During in vitro differentiation of hiPSCs into hematoendothelial progenitors, the emergence of CD34-positive cells indicates a critical step of lineage specification. To facilitate the monitoring of hematopoietic differentiation of hiPSCs, we established fluorescent reporter cells for the stem and progenitor cell marker CD34.