## 5 Multi-Level Visual Design and Analysis of RGN Predicted Results
### The Prediction Accuracy of the RGN  
At the level of RGN prediction accuracy, the prediction level of RGN is comprehensively analyzed through comparison standards and various statistical visualization charts, including the reasons for selecting comparison standards and analyzing the prediction accuracy according to the statistical information of comparison standards, observing the prediction of TBM data and FM data. The prediction results of the RGN obtain the prediction characteristics of the RGN through the evaluation of \(dRMSD\), \(TM\)-\(Score\), and \(GDT\_TS\), which provide guidance for the next two levels. In the evaluation stage of RGN, the parameters of RGN are optimized by adding a normalized \(dRMSD\) loss function to maximize the similarity between the predicted structure and the real structure. Therefore, when the structure prediction is completed, the \(dRMSD\) of the two structures is first calculated, and the similarity is analyzed. To visually observe the similarity between the two structures, the \(d_{ij}\) in the predicted structure chain and the real structure of the Formula (1) are respectively treated in the form of a distance matrix, and then the difference between each value in the two distance matrices is visualized as the distance matrix heat map. As shown in Figure 3a,b is the distance matrix heat map of the predicted structure and the real structure and Figure 3c is the distance matrix heat map of the corresponding position difference in the distance matrix of the predicted structure and the real structure. The abscissa and ordinate of these three heat maps are the indexes of residues in the structure. The value range is [1, _n_], \(n\) is the number of residues, and the mapping of the median value in the heat map is the distance between atoms in the  
Figure 3: Visualization of the distance matrix. The horizontal and vertical axis is the length of the certain protein chain, and each point represents the distance between the _i_th residue and the _j_th residue (the progressive color from blue to red indicates that the distance is getting farther). The \(dRMSD\) of this protein chain is obtained from the Matrix Heatmap. The more complex the chart, the larger the \(dRMSD\). (**a,b**) shows the distance matrix heat map of the predicted structure and the real structure. (**c**) shows the distance matrix heat map of the corresponding position difference in the distance matrix of the predicted structure and the real structure. complexity of the distance matrix difference heat map is mapped to the size of _dRMSD_. According to its calculation formula, the more complex the distance matrix difference heat map on the right side, the greater the _dRMSD_, and the worse the similarity between the predicted structure and the real structure. Moreover, when comparing the structures, the difference heat map of the distance matrix is analyzed first and then located in the local segments of the tertiary structure. As shown in the distance matrix visualization in Figure 3, because _dRMSD_ does not require pre-aligned structures, even if the global consistency is poor, regions with high similarity of a certain protein chain can be detected. In addition, it will detect all predictions within the length range and penalize large global deviations proportional to their distances, which may cause high errors for areas far apart. The prediction accuracy of RGN is analyzed. The similarity of each protein prediction chain was calculated according to the three comparison standard formulas, and all prediction data were classified as _GDT_TS_ standards are sorted from large to small, and then the similarity of the other two comparison standards under these two types of data is analyzed based on this order, and the statistical information is visualized by using appropriate visual charts. The following analyzes the overall prediction of RGN in CASP7. Figure 4 shows the ranking of the RGN prediction results according to the evaluation criteria of _GDT_TS_.