Download 424 peptides derived from the following papers:
  • Fernandez-Escamilla,A.M. et al. (2004).
    Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nat. Biotechnol., 22, 1302-1306.
  • Garbuzynskiy, S.O. et al.
    FoldAmyloid: a method of prediction of amyloidogenic regions from protein sequence Bioinformatics. 2010 Feb 1;26(3):326-32
  • Thompson,M.J. et al. (2006).
    The 3D profile method for identifying fibril-forming segments of proteins Proc. Natl. Acad. Sci. USA, 103, 4074-4078.
  • Roland, B.P. et al. (2013).
    A serendipitous survey of prediction algorithms for amyloidogenicity Biopolymers. 100(6):780-9. doi: 10.1002/bip.22305.
In total 424 peptides with the following lines:
peptide amino acids	+/-
+ denotes aggregating (149 in total) and - denotes non-aggregating (275 in total).

Download 33 proteins with annotated hotspots derived from the following paper:
  • Tsolis, A.C. et al. (2013).
    A Consensus Method for the Prediction of "Aggregation-Prone" Peptides in Globular Proteins PLoS ONE 8(1): e54175.
Each entry has the following lines:
Protein name
Amino acid sequence
start[i]-end[i] for all hot spots i=1,....n