Bioimage-based protein subcellular location prediction: a comprehensive review

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 patterns. Co...

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Published in:Frontiers of Computer Science Vol. 12; no. 1; pp. 26 - 39
Main Authors: XU, Ying-Ying, YAO, Li-Xiu, SHEN, Hong-Bin
Format: Journal Article
Language:English
Published: Beijing Higher Education Press 01.02.2018
Springer Nature B.V
Subjects:
Algorithms
Amino acids
Automation
bioimage informatics
Bioinformatics
Biomarkers
Cancer
Computer Science
Dynamic characteristics
global and local features
Imaging techniques
Localization
Machine learning
Microscopy
multi-location protein recognition
Pattern recognition systems
protein subcellular location prediction
Proteins
Protons
Review Article
bioimage informatics
protein subcellular location prediction
multi-location protein recognition
global and local features
ISSN:2095-2228, 2095-2236
Online Access:Get full text
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Abstract 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 patterns. 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 characteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systematically reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and classified them into four categories including growing of bioimage databases, description of subcellular location distribution patterns, classification methods, and applications of the prediction systems. Besides, we also discussed some potential directions in this field.
AbstractList 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 patterns. 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 characteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systematically reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and classified them into four categories including growing of bioimage databases, description of subcellular location distribution patterns, classification methods, and applications of the prediction systems. Besides, we also discussed some potential directions in this field.
Author XU, Ying-Ying
YAO, Li-Xiu
SHEN, Hong-Bin
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  surname: XU
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  givenname: Hong-Bin
  surname: SHEN
  fullname: SHEN, Hong-Bin
  email: hbshen@sjtu.edu.cn
  organization: Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China
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Copyright Copyright reserved, 2018, Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
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Keywords bioimage informatics
protein subcellular location prediction
multi-location protein recognition
global and local features
Language English
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Notes bioimage informatics
protein subcellular location prediction
multi-location protein recognition
Document accepted on :2016-11-02
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global and local features
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Snippet Subcellular localization of proteins can provide key hints to infer their functions and structures in cells. With the breakthrough of recent molecule imaging...
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SubjectTerms Algorithms
Amino acids
Automation
bioimage informatics
Bioinformatics
Biomarkers
Cancer
Computer Science
Dynamic characteristics
global and local features
Imaging techniques
Localization
Machine learning
Microscopy
multi-location protein recognition
Pattern recognition systems
protein subcellular location prediction
Proteins
Protons
Review Article
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Title Bioimage-based protein subcellular location prediction: a comprehensive review
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