ncRNA possesses little known specificity albeit with much potential to change cellular outcomes. We're building signatures that identify desirable cell states to educate Natural Killer cells. We presently focus on intron1. We compute all potential subsequence’s (k-mers) of seven or more nucleotides and count k-mer repeats. At each computational step, which starts at the first nucleotide each k-mer is paired to its transcript mRNA signature (m-sig) and ranked into a vector that represents multiple transcripts. For each transcript, k-mers are ordered by repeats and selected for the most significant change in the vector at the next row. Selected k-mers are grouped, deduplicated, identified to their intron1 positions, compared to miRNA or other databases and transfected to test biological results. We are building a signature database for laboratories to identify cells for use in autologous treatment.