Experiment data used in DeepHelicon

Published: 13 April 2020| Version 2 | DOI: 10.17632/k8tfvgftv3.2
Contributors:
jianfeng sunmt,
Dmitrij Frishman

Description

The data is for the paper titled "DeepHelicon: accurate prediction of inter-helical residue contacts in transmembrane protein by residual neural networks". It contains four sub-folders as follows: 1. Fasta: the protein sequences in the TRAIN, PREVIOUS, and TEST datasets, respectively. 2. PDB: the protein native structures in the TRAIN, PREVIOUS, and TEST datasets, respectively. 3. Predictions: the contact predictions on the PREVIOUS and TEST datasets, which are predicted by the contact prediction methods mentioned in the DeepHelicon paper. 4. 3D modelling: the 3D models, which are guided by the secondary structures predicted by SCRATCH1D and guided by the residue contacts predicted by DeepHelicon and DeepMetaPSICOV, respectively, are finally generated by CONFOLD2.

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