Cross-Beta RF predictor is a program for the prediction of amyloidogenicity based on the machine learning "Random Forest" model. It has been trained on naturally-occurring cross-β amyloids coming from the Cross-Beta DB as a positive dataset and Intrinsically Disordered Regions (IDRs) known to be soluble as a negative dataset.

Cross-Beta RF predictor can be used on amino acid sequences longer than 15 residues. It accepts as input simple sequences (without header), or FASTA sequences.


Please cite :
Valentin Gonay, Michael P. Dunne, Javier Caceres-Delpiano, & Andrey V. Kajava. (2024). Developing machine-learning-based amyloid predictors with Cross-Beta DB. bioRxiv, 2024.02.12.579644. https://doi.org/10.1101/2024.02.12.579644


Contact : valentin.gonay@crbm.cnrs.fr

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