Publication detail

pqsfinder web: G-quadruplex prediction using optimized pqsfinder algorithm

LABUDOVÁ, D. HON, J. LEXA, M.

Original Title

pqsfinder web: G-quadruplex prediction using optimized pqsfinder algorithm

Type

journal article in Web of Science

Language

English

Original Abstract

Motivation: G-quadruplex is a DNA form in which four guanine-rich regions are held together by Hoogsteen bonding between guanine nucleotides in coordination with potassium ions. G-quadruplexes are increasingly seen as a biologically important component of genomes. Their detection in vivo is problematic, however, sequencing and spectrometric techniques exist for in vitro detection in isolated DNA. In silico methods can be used to analyze nucleotide sequences for potential quadruplex-forming sequences (PQS). We previously devised the pqsfinder algorithm for identification of PQS, implemented it in C++ and published it as an R/Bioconductor package. We looked for ways to optimize pqsfinder for faster and user-friendly sequence analysis.Results: We identified two weak points where pqsfinder could be optimized. We modified the internals of the recursive algorithm to avoid matching and scoring many sub-optimal PQS conformations that are later discarded. To accommodate the needs of a broader range of users, we created a website for submission of sequence analysis jobs that does not require knowledge of R to use pqsfinder

Keywords

web application, G-quadruplex identification, G4, imperfect G4, potential quadruplex-forming sequence, PQS, pattern search

Authors

LABUDOVÁ, D.; HON, J.; LEXA, M.

Released

15. 4. 2020

ISBN

1367-4803

Periodical

BIOINFORMATICS

Year of study

36

Number

8

State

United Kingdom of Great Britain and Northern Ireland

Pages from

2584

Pages to

2586

Pages count

3

URL

https://www.fit.vut.cz/research/publication/12079/

BibTex

@article{BUT162286,
  author="Dominika {Labudová} and Jiří {Hon} and Matej {Lexa}",
  title="pqsfinder web: G-quadruplex prediction using optimized pqsfinder algorithm",
  journal="BIOINFORMATICS",
  year="2020",
  volume="36",
  number="8",
  pages="2584--2586",
  doi="10.1093/bioinformatics/btz928",
  issn="1367-4803",
  url="https://www.fit.vut.cz/research/publication/12079/"
}