The Cross-Beta DB compiles information on naturally occurring cross-beta-forming amyloids,
each substantiated by experimental evidence confirming the presence of the cross-beta structure.
The database can be used for training and benchmarking of methods that predict amyloid-prone regions in protein sequences.
Additionally, it provides supplementary data on experimental conditions and other relevant information for broader utilization.
Users can download entries from the database individually or in groups.
This database was used to develop Cross-Beta predictor, a machine-learning-based predictor of amyloidogenicity based on naturally occurring cross-beta-forming amyloids.
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