MIMLRBF预测谷物蛋白质功能方法的改进

随着人们对营养与保健功能的关注,谷物蛋白质功能预测已经成为当前研究热点.面对大量已完成测序的谷物蛋白质基因组数据,利用计算方法来预测谷物蛋白质功能已经成为主流.从谷物蛋白质结构域序列出发,首次将MIMLRBF算法运用到蛋白质功能预测,并在此算法基础上,提出了多种改进后的谷物蛋白质功能预测模型.其中,针对平均Hausdo...

Improvement of MIMLRBF Algorithm for Predicting Function of Grain Proteins

With people''s attention to nutrition and health care functions, the prediction of grain protein function has become a research hotspot. Faced with large amounts of sequenced cereal protein genome data, the use of computational methods to predict grain protein function has become the mainstream. For the first time, the MIMLRBF algorithm was applied to protein function prediction from the grain protein domain sequence. Based on this algorithm, several improved grain protein function prediction models were proposed. Among them, an automatic adjustment coefficient for the average Hausdorff distance was introduced to calculate the similarity between proteins aiming to solve the problem that the average Hausdorff distance weakened the shortest domain distance between two proteins. At the same time, in order to improve the prediction effect, the improved MIMLRBF algorithm model was obtained using the improved hybrid radial basis kernel function to activate. Finally, the improved MIMLRBF was confirmed to be better than the traditional prediction based on the evaluation of prediction results using mainstream evaluation criteria, which proved the superiority of the proposed model.