Search

This paper improves the performance of the model by Graph Convolutional Network (GCN) and Firefly Algorithm (FA) to optimize the financial investment risk prediction model. It studies the application of GCN in financial investment risk prediction model and elaborates on the role of FA in the model. To further improve the accuracy of the prediction model, this paper optimizes and improves the FA and verifies the effectiveness of the optimized model through experiments. Experimental results show that the optimized model performs well in feature selection, and the optimal accuracy of feature selection reaches 91.9%, which is much higher than that of traditional models. Meanwhile, in the analysis of the number of iterations of the model, the performance of the optimized algorithm gradually tends to be stable. When the number of iterations is 30, the optimal value is found. In the simulation experiment, when an unexpected accident occurs, the prediction accuracy of the model decreases, but the prediction performance of the optimized algorithm proposed here is significantly higher than that of the traditional model. In conclusion, the optimized model has high accuracy and reliability in financial investment risk prediction, which provides strong support for financial investment decision-making. This paper has certain reference significance for the optimization of financial investment risk prediction model. [ABSTRACT FROM AUTHOR]

Herpesvirus-associated ubiquitin-specific protease (HAUSP, also known as USP7), a deubiquitylating enzyme of the ubiquitin-specific processing protease family, specifically deubiquitylates both p53 and MDM2, hence playing an important yet enigmatic role in the p53-MDM2 pathway. Here we demonstrate that both p53 and MDM2 specifically recognize the N-terminal tumor necrosis factor-receptor associated factor (TRAF)-like domain of HAUSP in a mutually exclusive manner. HAUSP preferentially forms a stable HAUSP-MDM2 complex even in the presence of excess p53. The HAUSP-binding elements were mapped to a peptide fragment in the carboxy-terminus of p53 and to a short-peptide region preceding the acidic domain of MDM2. The crystal structures of the HAUSP TRAF-like domain in complex with p53 and MDM2 peptides, determined at 2.3-Å and 1.7-Å resolutions, respectively, reveal that the MDM2 peptide recognizes the same surface groove in HAUSP as that recognized by p53 but mediates more extensive interactions. Structural comparison led to the identification of a consensus peptide-recognition sequence by HAUSP. These results, together with the structure of a combined substrate-binding-and-deubiquitylation domain of HAUSP, provide important insights into regulation of the p53-MDM2 pathway by HAUSP. [ABSTRACT FROM AUTHOR]