In this paper,a novel method to automatically detect protein spots on a two-dimensional (2-D) electrophoresis gel image is proposed to implement proteomics analysis of complex analyte.On the basis of the identifying s...In this paper,a novel method to automatically detect protein spots on a two-dimensional (2-D) electrophoresis gel image is proposed to implement proteomics analysis of complex analyte.On the basis of the identifying spots results based on color variation and spot size features,morphological feature is introduced as a new criterion to distinguish protein spots from non-protein spots.Image-sharpening,edge-detecting and morphological feature extraction methods were consequently combined to detect protein spots on a 2-D electrophoresis gel image subject to strong disturbance.The proposed method was applied to detect the protein spots of proteomic gel images from E.coli cell,human kidney tissue and human serum.The results demonstrated that this method is more accurate and reliable than previous methods such as PDQuest 7.2 and ImageMaster 5.0 software for detecting protein spots on gel images with strong interferences.展开更多
基金the National Natural Science Foundat ion of China(Grant No.90209005) Science and Technology Project of Zhejiang Province(Grant No.2004C33026).
文摘In this paper,a novel method to automatically detect protein spots on a two-dimensional (2-D) electrophoresis gel image is proposed to implement proteomics analysis of complex analyte.On the basis of the identifying spots results based on color variation and spot size features,morphological feature is introduced as a new criterion to distinguish protein spots from non-protein spots.Image-sharpening,edge-detecting and morphological feature extraction methods were consequently combined to detect protein spots on a 2-D electrophoresis gel image subject to strong disturbance.The proposed method was applied to detect the protein spots of proteomic gel images from E.coli cell,human kidney tissue and human serum.The results demonstrated that this method is more accurate and reliable than previous methods such as PDQuest 7.2 and ImageMaster 5.0 software for detecting protein spots on gel images with strong interferences.
