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A review from biological mapping to computation-based subcellular localization.

Jing Li1,2, Quan Zou1, Lei Yuan3

  • 1Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, 1 Chengdian Road, Quzhou, Zhejiang 324000, China.

Molecular Therapy. Nucleic Acids
|May 22, 2023
PubMed
Summary
This summary is machine-generated.

This review synthesizes current literature on protein and RNA subcellular localization, crucial for understanding diseases and developing targeted drugs. It details methods for building predictive models, aiding biological and computational biology research.

Keywords:
MT: Bioinformaticsdeep learningdisease preventiondrug discoverymachine learningsubcellular localization

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Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Subcellular localization of proteins and RNA is vital for studying viruses, host interactions, and human diseases like Alzheimer's and colon cancer.
  • Existing reviews on protein subcellular localization are outdated, and RNA subcellular localization reviews lack comprehensiveness.
  • Understanding subcellular localization aids in targeted drug design and disease mechanism elucidation.

Purpose of the Study:

  • To provide an up-to-date collation of literature on both protein and RNA subcellular localization.
  • To summarize methods for constructing subcellular localization models using biological data.
  • To highlight the integration of biotechnology and computer science in this field.

Main Methods:

  • Comprehensive literature review of protein and RNA subcellular localization studies.
  • Systematic summary of methodologies for building subcellular localization predictive models.
  • Analysis of current trends and applications in biotechnology and computational biology.

Main Results:

  • The review is the first to cover both protein and RNA subcellular localization in a single, comprehensive resource.
  • It details the evolution and application of various techniques in subcellular localization modeling.
  • Identifies the need for further research into the interrelationships and causality between protein and RNA localization.

Conclusions:

  • This work serves as a critical reference for researchers in biology and computational biology.
  • It emphasizes the importance of understanding the dynamic interplay between protein and RNA subcellular localization.
  • Encourages collaborative research to explore transformation patterns and causal links in subcellular localization.