Systematic Evaluation of Feature Representations for Cancer-Associated sORF Prediction in Non-coding RNA
Fabiana Rodrigues de Góes, Makanaka Mazheke, Amanda Piveta Schnepper, Aparajita Karmakar, Nayane de Souza, Robson Francisco Carvalho, Mark Basham, Alexandre Rossi Paschoal
The paper evaluates feature representations for predicting cancer-associated sORFs in non-coding RNA using traditional machine learning models and finds that k-mer features outperform genomic language model embeddings.
bioRxiv · Jun 20, 2026 · PreprintBioinformatics