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.本数据集对应题为《DeepHelicon：基于残差神经网络（residual neural networks）的跨膜蛋白（transmembrane protein）螺旋间残基接触（inter-helical residue contacts）精准预测》的学术论文。该数据集包含四个子文件夹，具体如下： 1. FASTA文件集：分别收录训练集（TRAIN）、旧数据集（PREVIOUS）与测试集（TEST）的蛋白质序列； 2. PDB文件集：分别收录训练集、旧数据集与测试集的蛋白质天然三维结构； 3. 预测结果文件集：针对旧数据集与测试集，采用DeepHelicon论文中提及的残基接触预测方法生成的残基接触预测结果； 4. 三维建模文件集：本次生成的蛋白质三维模型共两类，分别以SCRATCH1D预测的蛋白质二级结构、以及DeepHelicon与DeepMetaPSICOV预测的残基接触作为引导信息，所有模型均由CONFOLD2最终生成。