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Bioimage-based protein subcellular location prediction: a comprehensive review 被引量:2

Bioimage-based protein subcellular location prediction: a comprehensive review
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摘要 Subcellular localization of proteins can provide key hints to infer their functions and structures in cells. With the breakthrough of recent molecule imaging techniques, the usage of 2D bioimages has become increasingly popular in automatically analyzing the protein subcellular location pat- terns. Compared with the widely used protein 1D amino acid sequence data, the images of protein distribution are more intuitive and interpretable, making the images a better choice at many applications for revealing the dynamic char- acteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systemati- cally reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and clas- sified them into four categories including growing of bioim- age databases, description of subcellular location distribution patterns, classification methods, and applications of the pre- diction systems. Besides, we also discussed some potential directions in this field. Subcellular localization of proteins can provide key hints to infer their functions and structures in cells. With the breakthrough of recent molecule imaging techniques, the usage of 2D bioimages has become increasingly popular in automatically analyzing the protein subcellular location pat- terns. Compared with the widely used protein 1D amino acid sequence data, the images of protein distribution are more intuitive and interpretable, making the images a better choice at many applications for revealing the dynamic char- acteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systemati- cally reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and clas- sified them into four categories including growing of bioim- age databases, description of subcellular location distribution patterns, classification methods, and applications of the pre- diction systems. Besides, we also discussed some potential directions in this field.
出处 《Frontiers of Computer Science》 SCIE EI CSCD 2018年第1期26-39,共14页 中国计算机科学前沿(英文版)
关键词 bioimage informatics protein subcellular loca-tion prediction global and local features multi-location pro-tein recognition bioimage informatics, protein subcellular loca-tion prediction, global and local features, multi-location pro-tein recognition
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