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Related Concept Videos

Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
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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. 
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Riboswitches are non-coding mRNA domains that regulate the transcription and translation of downstream genes without the help of proteins. Riboswitches bind directly to a metabolite and can form unique stem-loop or hairpin structures in response to the amount of the metabolite present. They have two distinct regions – a metabolite-binding aptamer and an expression platform.
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Related Experiment Video

Updated: Dec 10, 2025

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
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rboAnalyzer: A Software to Improve Characterization of Non-coding RNAs From Sequence Database Search Output.

Marek Schwarz1, Jiří Vohradský1, Martin Modrák1

  • 1Laboratory of Bioinformatics, Institute of Microbiology, Czech Academy of Sciences, Prague, Czechia.

Frontiers in Genetics
|August 28, 2020
PubMed
Summary

rboAnalyzer enhances bioinformatics sequence searches by extending partial RNA matches into full-length sequences. This tool improves homology identification and secondary structure prediction for non-coding RNAs.

Keywords:
RNARNA homologydatabasesearchsecondary structuresequence

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Sequence similarity searching is crucial in bioinformatics, especially for non-coding RNAs.
  • Interpreting BLAST results can be challenging due to partial sequence matches.

Purpose of the Study:

  • To develop rboAnalyzer, a tool for improved interpretation of sequence search results.
  • To address the challenge of partial matches in bioinformatics sequence analysis.

Main Methods:

  • Extending partial sequence matches to plausible full-length sequences.
  • Predicting RNA homology and pooling information from search results and databases like Rfam.
  • Generating a rich graphical output for contextualizing matches.

Main Results:

  • rboAnalyzer successfully extends partial matches to full-length sequences.
  • Improved secondary structure prediction using full-length matches.
  • Robust identification of RNA homology and reliable characterization of non-coding RNAs.

Conclusions:

  • rboAnalyzer provides a robust method for interpreting sequence search results, particularly for non-coding RNAs.
  • The tool enhances secondary structure prediction and homology identification through its analytical capabilities.
  • rboAnalyzer facilitates reliable characterization of RNA sequences in BLAST outputs.