Figure 1.

Predicting aptamer sequence using Smart-SELEX: (a) training the machine learning model using data collected from the literature data, (b) generating the initial RNAs library (10⁸), (c) filtering the sequences by calculating the free energy and increasing the number of the loops, (d) using the machine learning model developed to predict the binding probability of each sequence with the analyte and ranking them from high to low, (e) docking the sequences with the positive and negative analytes and calculating the binding energy, and (f) the final aptamer with high affinity towards the target.