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Showing 2 results for Elastic Network
Volume 16, Issue 1 (3-2016)
Abstract
Conformational changes during protein -protein or ligand -protein docking play an important role in the biological processes. These changes involve low frequency collective motions, and normal mode analysis is generally used for finding the frequencies and mode shapes of the proteins. Many studies have been focused on the prediction of these transitions using different protein models. Among them, elastic network models are popular, as they are simple and do not require energy minimization. However, so far no systematic study has been done about considering the effect of different parameters in prediction of these conformational changes. In this study 20 proteins with pre-determined conformational changes were selected and the success and validation of each elastic network model in predicting the bound state were tested. According to the results, the first three modes play the major role in predicting the conformational changes. Moreover, choosing the proper cutoff radius is more effective than the potential function. Results also show that non-exponential models with 10 angestrom cutoff are more accurate in predicting conformational changes, in spite of their simplicity and being less time consuming.
Dr Amirreza Souri, Mrs Fatemeh Panahi,
Volume 25, Issue 1 (3-2025)
Abstract
Aim and Introduction
The purpose of this article is to compare two methods of bilateral differences and individual variables to investigate the impact of macroeconomic variables on the exchange rate. The model used in the research is the monetary model with sticky prices (SPMM), which is used in order to improve the accuracy of the estimates from the Elastic Net. Research variables include exchange rate, gross domestic product (GDP), real interest rate (IR), consumer inflation (IN) and liquidity (M2) for two groups of developed and less developed countries. It has been estimated seasonally during the period from 1996 to 2022.
Methodology
The model used in this article is the modified model of Biswas et al. (2022) and by using the SPMM model, the impact of macroeconomic variables on the exchange rate for developed and less developed countries is estimated in the form of bilateral difference methods and individual variables. In this regard, the model simulation analysis is explained first, and then the SPMM model is estimated and described using the variables of bilateral differences and individual variables.
Results and Discussion
The results of the research show that when the real model uses individual variables, the estimation of the model using the two-sided differences method increases the mean square error (MSE), and when the real model uses two-sided differences, the estimation of the model using the ndividual variables method produce higher MSE. In general, the findings of the research show that using individual variables to estimate the real model is more accurate, but the accuracy of the estimates may decrease in certain conditions. Therefore, it is important to consider various factors such as true model complexity, error term size, and sample size when choosing between individual variables and pairwise differences.
Conclusion
Other research findings show that model estimation using individual variables and elastic network leads to lower MSE than bilateral differences. In addition, the reduction of MSE among less developed countries are more than that of developed countries. Also, the impact of macroeconomic variables on the exchange rate is stronger in less developed countries than in developed countries
