Medical image analysis of phosphorylated protein interaction extraction algorithm based on text mining technology

• Published in: Multimedia tools and applications Vol. 79; no. 15-16; pp. 10551 - 10579
• Main Authors: Ma, Xiaolei, Lu, Yang, Lu, Yinan, Pei Zhili
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Nature B.V 01.04.2020
• Subjects: Algorithms; Bioinformatics; Biological activity; Data mining; Image analysis; Image segmentation; Medical imaging; Proteins
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-019-07853-1

Medical images have been widely used in the analysis of phosphorylated protein interactions, Medical image segmentation separates different regions of a particular meaning in an image. These regions make each region that does not intersect with each other satisfy the consistency of a particular region. In bioinformatics, measurement on protein interaction is one of the key points, which plays a very important role in understanding various biological processes and in the treatment and diagnosis of diseases. The physiological functions of organisms are mainly regulated by proteins in cells, so studying the interaction between proteins becomes the basis for understanding life activities. Using text mining methods to study protein interactions can make full use of the vast literature available to reveal potential knowledge associated with proteins and construct protein interaction networks. Therefore, this paper proposes a method for automatically extracting protein interaction pairs from the literature by studying the extraction principle of protein interactions and their interaction words. At the same time, the method of protein interaction relationship mining is developed. The research and the results obtained in this paper have certain reference value for the study of protein relations in the future.