基于Spiking神经网络的蛋白质二级结构学习预测模型  

Protein Secondary Structure Learning and Prediction Model based on Spiking Neural Network

作　　者：沈虹[1] SHEN Hong （Golden Audit College of Nan jing Audit University,Nanjing 211815,China）

机构地区：[1]南京审计学院金审学院,江苏南京211815

出　　处：《电脑知识与技术》2007年第11期683-684,共2页Computer Knowledge and Technology

摘　　要：从氨基酸序列来预测蛋白质二级结构，是我们理解蛋白质结构和功能的重要一步。本文探讨了基于Spiking神经网络的蛋白质二级结构学习预测模型，利用单个神经网络进行学习取得的效果不明显，而利用级联神经网络，通过结构到结构的学习，能很好地提高学习准确率。Predicting the protein secondary structure from amino acids sequenct is an important step, from which we can comprehend protein structure and function. This paper discussed the secondary structure learning and prediction model based on Spiking neural network. The result shows the learning effect through single neural network is not good. While learning from structure by multi-level Spiking neural network, the learning accuracy can be greatly improved.

关 键 词：蛋白质二级结构 神经网络 学习预测模型 

分 类 号：TP393[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]