CRSOM is a ncRNAs classifier using heterogeneous sources. CRSOM combines self-organizing maps (SOM), which is an unsupervised learning algorithm, with a multilayer peceptrons (MLP) that is a supervised learning algorithm. CRSOM learns the source weights locally at the level of a cluster and uses rejection options in order to improve the reliability of the predictions and to identify potential new classes.