Before revision:  Here, we present an RNA design agent , SentRNA, which consists of a fully-connected neural network trained using the eternasolves dataset, a set of 1.8 x 10^4 player-submitted sequencesacross 724 unique targets. The agent first predicts an initial sequence for a target using the trained network, and then refines that solution if necessary using a short adaptive walk utilizing a canon of standard design moves. Through this approach, we observe SentRNA can learn and apply human-like design strategies to solve several complex targets previously unsolvable by any computational approach .
After revision:  Here, we present an RNA design agent , SentRNA, which consists of a fully-connected neural network trained end-to-end using human-designed RNA sequences. We show that through this approach, we observe SentRNA can learn and apply human-like design strategies to solve several complex targets previously unsolvable by any computational approach .