ElTetrado
ElTetrado identifies and classifies tetrads and quadruplexes in nucleic acid 3D structures to analyze secondary-structure topology of canonical and non-canonical quadruplex motifs relevant to telomeres and transcriptional regulatory regions.
Key Features:
- Identification: Detects tetrads and quadruplexes by analyzing base-pairing patterns in DNA and RNA 3D structures.
- Classification (ONZ taxonomy): Classifies tetrads and quadruplexes according to the ONZ taxonomy based on secondary-structure topology.
- Secondary-structure topology analysis: Uses secondary-structure topology to distinguish between different structural configurations of tetrads and quadruplexes.
- Support for canonical and non-canonical motifs: Accommodates both canonical and non-canonical quadruplex motifs.
- Notation and visualization outputs: Generates dot-bracket notation and graphical depictions that reflect the unique secondary-structure topology of identified quadruplexes.
Scientific Applications:
- Telomere studies: Characterizes tetrads and quadruplexes present in telomeric regions.
- Transcriptional regulation: Analyzes quadruplex motifs in transcriptional regulatory regions to support studies of gene regulation.
- Non-canonical motif characterization: Enables analysis of non-canonical quadruplexes beyond canonical sequence-focused approaches.
- Complementary structural analysis: Provides secondary-structure topology insights that complement sequence and 3D structural examinations.
Methodology:
Analyzes base-pairing patterns in DNA/RNA 3D structures to identify tetrads and quadruplexes, classifies motifs using secondary-structure topology according to the ONZ taxonomy, and outputs dot-bracket notation and graphical depictions.
Topics
Details
- License:
- MIT
- Tool Type:
- command-line tool
- Programming Languages:
- Python, R
- Added:
- 1/18/2021
- Last Updated:
- 3/5/2021
Operations
Publications
Zok T, Popenda M, Szachniuk M. ElTetrado: a tool for identification and classification of tetrads and quadruplexes. BMC Bioinformatics. 2020;21(1). doi:10.1186/s12859-020-3385-1. PMID:32005130. PMCID:PMC6995151.