A new intelligent prediction system model-the compound pyramid model

• Published in: Science China. Information sciences Vol. 55; no. 3; pp. 723 - 736
• Main Authors: Yang, BingRu, Qu, Wu, Wang, LiJun, Zhou, Ying
• Format: Journal Article
• Language: English
• Published: Heidelberg SP Science China Press 01.03.2012; Springer Nature B.V
• Subjects: Cellular automata; Cellular structure; China; Computer Science; Construction; Datasets; Information Systems and Communication Service; Intelligent systems; Mathematical models; Multilayers; Predictions; Proteins; Pyramids; Research Paper; 元胞自动机; 多层复合; 智能系统; 智能预报系统; 结构数据库; 蛋白质结构预测; 金字塔模型; 预测系统模型; intelligent prediction system model; knowledge discovery; compound pyramid model
• ISSN: 1674-733X; 1869-1919
• DOI: 10.1007/s11432-011-4442-1

A current development trend in research on intelligent systems is to optimize a general intelligent prediction system into an individuation intelligent prediction system that is applied in specialized fields. Protein structure prediction is a challenging international issue. In this paper, we propose a new intelligent prediction system model, designed as a multi-layer compound pyramid model, for predicting secondary protein structure. The model comprises four independent intelligent interfaces and several knowledge discovery methods. The model penetrates throughout the domain knowledge, with the effective attributes chosen by Causal Cellular Automata. Furthermore, a high pure structure database is constructed for training. On the RS126 dataset, the overall state per-residue accuracy, Q3, reached 83.99%, while on the CB513 dataset, Q3 reached 85.58%. Meanwhile, on the CASP8 sequences, the results are superior to those produced by other methods, such as Psipred, Jpred, APSSP2 and BehairPred. These results confirm that our method has a strong generalization ability, and that it provides a model for the construction of other intelligent systems.