Bioinformatics-Based Modeling and Prediction of the Effects of Heavy Metal Drugs on Acute Liver Toxicity

Abstract

Heavy metal pollution can cause a series of diseases, especially the liver, which becomes the main target of toxicity. In order to be able to accurately predict the effects of heavy metals on the liver, this paper is based on bioinformatics firstly, the pollution level of heavy metals and the effects on the liver were analyzed, and the relationship between the characteristics of heavy metals and the liver was derived. Secondly, the toxicity of heavy metals was tested to get the toxicity content in different heavy metals. Finally, a toxicity prediction model was established based on the toxicity data to facilitate the analysis of the effects of heavy metals on the liver and to reduce the hazards of heavy metals on the human body. The analysis was carried out in three parts: prediction accuracy, prediction model performance and the effect of heavy metals on the liver, and it was concluded that the prediction ability of the model was better, and the values of the mean squared error and the root squared error were smaller, around 0.483 and 0.161, which indicated that the actual value was similar to the test value, and the comparison found that the heavy metal Cd had a greater effect on the function of the liver, and the value of the alanine aminotransferase was increased to 0.47, which can show the complete the concentration of toxicity and the effect on the liver.