Supplement for manuscript entitled "Sequence-only based prediction of β-turn location and type using collocation of amino acid pairs"

Supplement for manuscript entitled "Sequence-only based prediction of beta-turn location and type using collocation of amino acid pairs"

This web page provides datasets associated with

Campbell K, Kurgan LA, 2008. Sequence-only based prediction of beta-turn location and type using collocation of amino acid pairs. Open Bioinformatics Journal, 2:37-49

The 565 dataset that was used to perform feature selection can be downloaded from here: 565 dataset

This dataset wes originally published in M. Asgary, S. Jahandideh, P. Abdolmaleki, and A. Kazemnejad 2007. Analysis and prediction of β-turn types using multinomial logistic regression and artificial neural network. Bioinformatics, 23(23):3125-3130.

Each sequence in this set is represented by 8 lines

- chain identifier (using PDB id)
- sequence (using 1-letter encoding of amino acids)
- annotation of location of type I beta-turns (T denotes the location of the turns)
- annotation of location of type II beta-turns (T denotes the location of the turns)
- annotation of location of type IV beta-turns (T denotes the location of the turns)
- annotation of location of type VII beta-turns (T denotes the location of the turns)
- annotation of location of NS (non-specific) type beta-turns (T denotes the location of the turns)
- last line identifies the non-beta-turns sampled and converted to features to perform feature selection

The 426 dataset that was used to perform evaluation and comparison with competing methods can be downloaded from here: 426 dataset

This dataset wes originally published in K. Guruprasad and S. Rajkumar, 2000. Beta- and gamma-turns in proteins revisited, a new set of amino acid turn-type dependent positional preferences and potentials. J Biosci, 25:143-156.

Each sequence in this set is represented by 3 lines

- chain identifier (using PDB id)
- sequence (using 1-letter encoding of amino acids)
- annotation of location of beta-turns types where each number corresponds to the tetrapeptide starting at the same position in the sequence with the following encoding: 0 -> no turn, 1 -> type I, 2 -> type II, 3 -> type VIII, 4 -> type I', 5 -> type II', and 6 -> type IV .

We also provide three variants of this dataset

- The dataset divided into 7 folds where tetrapeptides were converted into features (all 1300 features) without sampling, can be downloaded from here: 426 dataset - 7 folds - all features - no sampling
- The dataset divided into 7 folds where tetrapeptides were converted into 50 selected features without sampling, can be downloaded from here: 426 dataset - 7 folds - 50 features - no sampling
- The dataset divided into 7 folds where tetrapeptides were converted into 50 selected features with 8% sampling, can be downloaded from here: 426 dataset - 7 folds - 50 features - 8% sampling