蛋白质三维空间结构固有的复杂性给其结构分类带来了较大的困难。将蛋白质空间结构映射成为二维距离矩阵,并进一步视作灰度纹理图像,使用拉冬变换分析了该图像的纹理方向特性,基于灰度共生矩阵和Radon投影矩阵提出了一种低维的蛋白质结构特征提取方法。实验结果与对比表明,该方法不仅具有低维的特征,而且有效地实现了多类蛋白质结构分类识别。
The intrinsic complexity of Protein Spatial Structure(PSS) brings a heavy difficulty to its structural classification. In this paper,PSS is mapped into 2-D distance matrix and further regarded as texture image of which textural directions are detected by Radon transform.Consequently, a novel method of feature extraction of PSS with low dimension is proposed based on gray level co-occurrence matrix and Radon transform project matrix.The experiments and the comparison results demonstrate that the presented method can not only product low-dimensional feature and also achieve effective classification of PSS.