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Non-Coding RNA Analysis Using the Rfam Database.

Ioanna Kalvari1, Eric P Nawrocki2, Joanna Argasinska1

  • 1European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.

Current Protocols in Bioinformatics
|June 22, 2018
PubMed
Summary
This summary is machine-generated.

Rfam is a comprehensive database for non-coding RNA families, providing computational models derived from scientific literature. It aids in annotating RNA sequences and supports genome research and algorithm development.

Keywords:
InfernalRNA familyRfamgenome annotationnon-coding RNA

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Area of Science:

  • Bioinformatics
  • Molecular Biology
  • Genomics

Background:

  • Non-coding RNAs (ncRNAs) play crucial roles in cellular processes.
  • Identifying and classifying ncRNA families is essential for understanding their functions.
  • Existing literature often contains dispersed information on ncRNA families.

Purpose of the Study:

  • To introduce the Rfam database as a centralized resource for ncRNA families.
  • To explain the methodology behind Rfam's data curation and model generation.
  • To guide users on accessing and utilizing Rfam for sequence annotation and research.

Main Methods:

  • Rfam utilizes a combination of manual curation and a custom software pipeline.
  • It integrates information from scientific literature, figures, and supplementary files.
  • Covariance models are generated from multiple sequence alignments and consensus secondary structures.

Main Results:

  • Rfam provides accessible computational models for numerous ncRNA families.
  • The database facilitates the annotation of ncRNAs in large DNA and RNA sequences.
  • Rfam data serves as valuable training sets for developing new algorithms.

Conclusions:

  • Rfam is a vital resource for researchers studying non-coding RNAs.
  • The database enhances ncRNA discovery and functional annotation.
  • Rfam promotes advancements in genomics and bioinformatics through accessible data.