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This repository contains the source code, simulation data, and documentation for the **RAISING**, a two-stage neural network(NN) implementation framework that first performs hyperparameter tuning to devise the best NN architecture and then performs training on the entire data to estimate the feature importance. The method has been published in Nucleic Acids Research (<https://doi.org/10.1093/nar/gkae1027>).