We developed a machine-learning model that integrates sequence (putative TF motifs, dinucleotide content) and epigenomic features (ATAC, methylation, proximal activity) to predict NSC<->IPC specificity of CREs, that yields R^2 = 0.62 on held-out data. 10/14