Experiment data used in DeepHelicon

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.

本数据集旨在支持名为《DeepHelicon：通过残差神经网络准确预测跨膜蛋白中螺旋间残基相互作用》的论文研究。数据集包含以下四个子文件夹：
1. Fasta：分别包含TRAIN、PREVIOUS和TEST数据集中的蛋白质序列。
2. PDB：分别包含TRAIN、PREVIOUS和TEST数据集中的蛋白质天然结构。
3. Predictions：对PREVIOUS和TEST数据集的接触预测，这些预测由DeepHelicon论文中提到的接触预测方法完成。
4. 3D建模：由SCRATCH1D预测的二级结构引导，并由DeepHelicon和DeepMetaPSICOV预测的残基相互作用引导，最终由CONFOLD2生成3D模型。