Gel protein partitioning method based on fuzzy clustering

Abstract

The invention discloses a gel protein partitioning method based on fuzzy clustering. The method comprises the steps that first, images are filtered, and the contrast ratio of the images is enhanced; second, the number of clustering categories, weighted indexes, an iteration termination threshold value, the maximum number of iterations and an initial clustering center are initialized; third, a radial width value in a kernel function is calculated; fourth, a membership matrix and a clustering center are updated; fifth, whether an absolute difference value of the current new clustering center and the last clustering center is smaller than the iteration termination threshold value or whether a current value of an iteration counter is greater than the maximum number of iterations is judged through comparison, if yes, the process is stopped, a final membership matrix and a final clustering center are output, and the sixth step continues to be executed, or else the fourth step continues to be executed after the iteration counter adds one; sixth, defuzzification is performed to obtain an optimal partitioning result. Through the method, noise eliminating ability is improved, relatively weak protein spots can be separated, and consequently more protein spots are separated; moreover, the method has a good separation effect on lightly-overlapping protein spots and has high partitioning precision.

Description

technical field [0001] The invention relates to the technical field of two-way gel image analysis, in particular to a gel protein segmentation method based on fuzzy clustering. Background technique [0002] Among many protein separation methods, two-dimensional gel electrophoresis (2-DE) technology is widely used in proteomics. It is mainly based on the difference in protein isoelectric point and molecular weight, and the proteins in the complex protein mixture are separated on a gel. Separation in the form of dots. The protein gel is then scanned using a scanning device to obtain a digitized gel image. On the image, proteins appear as dots with different shapes, sizes and grayscales, each of which represents a specific protein. Segmentation is an important step in image analysis. The study of gel images needs to extract protein spots from the image. Its main goal is to find the position of protein spots and the boundaries around protein spots, determine their number and a...

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Problems solved by technology

[0009] At present, there is no in-depth research on gel image segmentation in China. Looking at the research status abroad, various methods have advantages and disadvantages, so what we have to do is to study the characteristics of protein spots in gel images. Advanced segmentation algorithm, while protecting image information and details, enhances the identification and detection of weak protein spots and overlapping protein spots

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