ArticleNucleic acids research2013
SPARCS: a web server to analyze (un)structured regions in coding RNA sequences.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Infrared: a declarative tree decomposition-powered framework for bioinformatics.Algorithms for molecular biology : AMB · 2024Article
- Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis.NPJ biofilms and microbiomes · 2023Article
- Theoretical basis for stabilizing messenger RNA through secondary structure design.Nucleic acids research · 2021Article
- Mechanisms and consequences of subcellular RNA localization across diverse cell types.Traffic (Copenhagen, Denmark) · 2020Review
- Fixed-parameter tractable sampling for RNA design with multiple target structures.BMC bioinformatics · 2019Article
- Article
- A code for transcription elongation speed.RNA biology · 2018Article
- Evidence of translation efficiency adaptation of the coding regions of the bacteriophage lambda.DNA research : an international journal for rapid publication of reports on genes and genomes · 2017Article
- Widespread signatures of local mRNA folding structure selection in four Dengue virus serotypes.BMC genomics · 2015Article
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
Abstract
More than a simple carrier of the genetic information, messenger RNA (mRNA) coding regions can also harbor functional elements that evolved to control different post-transcriptional processes, such as mRNA splicing, localization and translation. Functional elements in RNA molecules are often encoded by secondary structure elements. In this aticle, we introduce Structural Profile Assignment of RNA Coding Sequences (SPARCS), an efficient method to analyze the (secondary) structure profile of protein-coding regions in mRNAs. First, we develop a novel algorithm that enables us to sample uniformly the sequence landscape preserving the dinucleotide frequency and the encoded amino acid sequence of the input mRNA. Then, we use this algorithm to generate a set of artificial sequences that is used to estimate the Z-score of classical structural metrics such as the sum of base pairing probabilities and the base pairing entropy. Finally, we use these metrics to predict structured and unstructured regions in the input mRNA sequence. We applied our methods to study the structural profile of the ASH1 genes and recovered key structural elements. A web server implementing this discovery pipeline is available at http://csb.cs.mcgill.ca/sparcs together with the source code of the sampling algorithm.
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Registered trials
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