I am trying to find some training dataset for prediction of Secondary Structure of Protein. I am having problems finding them online.
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The standard benchmark dataset is the one from Lindahl, which consists of 976 × 975 target-template protein pairs.
Lindahl, E. & 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.
