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lncRNA - Long Non-coding RNAs02:39

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A Protocol for Computer-Based Protein Structure and Function Prediction
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Computational models for lncRNA function prediction and functional similarity calculation.

Xing Chen1, Ya-Zhou Sun2, Na-Na Guan2

  • 1School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.

Briefings in Functional Genomics
|September 25, 2018
PubMed
Summary

Long non-coding RNAs (lncRNAs) are crucial in complex diseases. This review details computational models for predicting lncRNA functions and similarity, aiding disease research and biomarker discovery.

Keywords:
computational modeldatabasediseasefunction predictionfunctional similarity calculationlong non-coding RNA

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Long non-coding RNAs (lncRNAs) play significant roles in human complex diseases, but their functions are not fully understood.
  • Abnormal lncRNA expression is linked to diseases like cancers and nervous system disorders.
  • Accurate functional annotation of lncRNAs is vital for disease pathology, diagnosis, and therapy.

Purpose of the Study:

  • To review computational models for predicting lncRNA functions and calculating functional similarity.
  • To provide an overview of lncRNA-related databases and their applications.
  • To discuss the advantages, limitations, and future directions in lncRNA computational analysis.

Main Methods:

  • Systematic review of 17 lncRNA function-related databases.
  • Description and classification of 16 lncRNA function prediction models.
  • Analysis of 9 lncRNA functional similarity calculation models based on their algorithms.

Main Results:

  • lncRNAs are involved in five key biological processes.
  • Computational models offer effective means to predict lncRNA functions and functional similarity on a large scale.
  • The review categorizes models based on core algorithms and processes.

Conclusions:

  • Computational models are essential tools for deciphering lncRNA functions and their roles in complex diseases.
  • Developing systematic functional annotation systems will enhance prediction accuracy.
  • Future research should focus on improving computational models for accelerated lncRNA discovery.