RNAConSLOpt

RNAConSLOpt predicts consensus stable local optimal (SLO) structures represented by stack configurations within aligned non-coding RNA (ncRNA) sequence families to identify conserved alternate native structures across related RNAs.


Key Features:

  • Consensus SLO stack generation: Generates all consensus SLO stack configurations conserved on the consensus energy landscape of related ncRNAs.
  • Structural conservation integration: Integrates structural conservation across aligned ncRNA sequences to prioritize conserved stack configurations and reduce candidate structures relative to RNASLOpt.
  • Energy landscape analysis: Analyzes the consensus energy landscape to predict alternate native structures.
  • Riboswitch candidate identification: Applied to identify novel riboswitch candidates in bacterial species, specifically within the Bacillus genus.

Scientific Applications:

  • ncRNA structural diversity analysis: Predicts alternate native structures conserved across related ncRNA sequences to study the structural basis of RNA function and regulation.
  • Riboswitch discovery: Identifies candidate riboswitches and regulatory elements in bacterial genomes, exemplified by discoveries in Bacillus.
  • Comparative analysis of RNA families: Supports comparative studies of aligned ncRNA families to reveal conserved local optimal stack configurations.

Methodology:

Performs comparative analysis of aligned RNA sequences within ncRNA families, focuses on conserved stack configurations, generates consensus SLO stack configurations, and analyzes the consensus energy landscape to identify stable local optimal structures.

Topics

Details

Tool Type:
command-line tool
Operating Systems:
Linux
Added:
8/3/2017
Last Updated:
11/25/2024

Operations

Publications

Li Y, Zhong C, Zhang S. Finding consensus stable local optimal structures for aligned RNA sequences and its application to discovering riboswitch elements. International Journal of Bioinformatics Research and Applications. 2014;10(4/5):498. doi:10.1504/ijbra.2014.062997. PMID:24989865. PMCID:PMC4156590.

Documentation

Links