Cross-Beta predictor - Amyloidogenicity predictor based on a machine learning approach

The model has been trained on a positive set including amino acid sequences derived from naturally-occurring cross-β amyloids from the Cross-Beta DB and a negative dataset containing Intrinsically Disordered Regions (IDRs) known to be soluble.

Citing Cross-Beta predictor:
Gonay V, Dunne MP, Caceres-Delpiano J, Kajava AV. Developing machine-learning-based amyloidogenicity predictors with Cross-Beta DB. Alzheimer's Dement. 2025; 1-7. https://doi.org/10.1002/alz.14510

Contact : valentin.gonay@crbm.cnrs.fr

Paste one protein sequence (Example):

NOTE : Maximum 1000 characters

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All scores above this value will be considered positive (amyloid).


This value can either be "auto" or must be equal to or less than the length of the query sequence. The "auto" value will take a window of size = 10% of the sequence length with a minimum of 15 and a maximum of 50.

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