iRSpot-PseDNC

iRSpot-PseDNC predicts recombination hotspots and coldspots from DNA sequences using a pseudo dinucleotide composition (PseDNC) feature representation to support studies of meiotic recombination and genome evolution.

Key Features:

• Prediction target: Identifies recombination hotspots and coldspots in genomic DNA sequences.
• Feature representation: Uses pseudo dinucleotide composition (PseDNC) as the primary feature vector.
• DNA structural properties: Incorporates six local DNA structural properties—twist, tilt, roll, shift, slide, and rise—into the PseDNC representation.
• Benchmarking: Evaluated on a Saccharomyces cerevisiae dataset using the jackknife test, achieving an overall success rate exceeding 82%.
• Extensibility: The PseDNC framework is adaptable to other genomes and broader DNA-related research applications.

Scientific Applications:

• Recombination mapping: Predicts locations of meiotic recombination hotspots and coldspots to support studies of recombination mechanisms.
• Genome evolution: Facilitates analysis of the role of recombination in genome evolution.
• DNA-related research: Provides a PseDNC-based approach applicable to broader DNA sequence analyses.

Methodology:

Represents sequences using pseudo dinucleotide composition (PseDNC) incorporating six local DNA structural properties (twist, tilt, roll, shift, slide, rise) and evaluated predictive performance with the jackknife test on a Saccharomyces cerevisiae dataset.