Training Data for Secondary Protein Structure prediction using neural network
The standard benchmark dataset is the one from Lindahl, which consists of 976 × 975 target-template protein pairs.


  Lindahl, E. &amp; Elofsson, A. Identification of related proteins on family, superfamily and fold level. Journal of molecular biology 295, 613–625 (2000).


It is for example used in the following articles:


Improving Protein Fold Recognition by Deep Learning Networks
Improving protein fold recognition by random forest


Another resource is SCOP: Structural Classification of Proteins.


  Nearly all proteins have structural similarities with other proteins and, in some of these cases, share a common evolutionary origin. The SCOP database, created by manual inspection and abetted by a battery of automated methods, aims to provide a detailed and comprehensive description of the structural and evolutionary relationships between all proteins whose structure is known. As such, it provides a broad survey of all known protein folds, detailed information about the close relatives of any particular protein, and a framework for future research and classification.