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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Identification of Circular RNAs using RNA Sequencing
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Identification of Circular RNAs using RNA Sequencing

Published on: November 14, 2019

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The bioinformatics toolbox for circRNA discovery and analysis.

Liang Chen1, Changliang Wang2, Huiyan Sun3

  • 1Department of Computer Science, Key Laboratory of Intelligent Manufacturing Technology of Ministry of Education, Shantou University.

Briefings in Bioinformatics
|February 28, 2020
PubMed
Summary
This summary is machine-generated.

Circular RNAs (circRNAs) are versatile RNA molecules with growing applications as disease biomarkers. This review surveys over 100 bioinformatics tools for circRNA analysis, aiding research and development in the field.

Keywords:
bioinformatics toolscircRNAdisease biomarkernext generation sequencingnon-coding RNAtext mining

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Genomics

Background:

  • Circular RNAs (circRNAs) are formed by back-splicing of linear RNA and have garnered significant attention.
  • Advances in sequencing and bioinformatics have expanded the understanding of circRNA types and functions.
  • CircRNAs show promise as biomarkers for various human diseases.

Purpose of the Study:

  • To compile and summarize available bioinformatics tools for circRNA research.
  • To analyze the capabilities and attributes of approximately 100 circRNA-associated tools.
  • To identify trends in the development of circRNA bioinformatics tools through network and text mining analysis.

Main Methods:

  • Systematic collection of circRNA-associated bioinformatics tools.
  • Summarization of tool attributes and functionalities.
  • Network analysis and text mining of publications related to circRNA tools.

Main Results:

  • A comprehensive catalog of ~100 circRNA bioinformatics tools was curated.
  • Current capabilities in circRNA annotation, identification, and competing endogenous RNA (ceRNA) network analysis were detailed.
  • Identified key trends and developmental trajectories in the circRNA bioinformatics landscape.

Conclusions:

  • Bioinformatics tools are crucial for advancing circRNA research and applications.
  • The reviewed tools support diverse aspects of circRNA analysis, from identification to functional studies.
  • Ongoing development in this field is driven by technological advancements and the pursuit of circRNA-based diagnostics.