Exons and introns characterization in nucleic acid sequences by time-frequency analysis.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Accurate gene localization and annotation in DNA sequences, particularly protein-coding regions in eukaryotic pre-mRNA, remain a challenge.
• Current methods require precise identification of gene structures within genomic data.

Purpose of the Study:

• To develop a numerical approach for gene localization and annotation using thermodynamic properties of nucleotide sequences.
• To identify pre-mRNA sequence features that effectively discriminate coding from non-coding regions.

Main Methods:

• Nucleotide sequences were converted into numerical values using thermodynamic free energy changes (ΔG°) for duplex formation.
• Time-frequency representation techniques were applied to analyze these numerical sequences.
• Instantaneous frequency and spectral energy variables were extracted for classification.

Main Results:

• The numerical conversion effectively represented pre-mRNA sequences.
• Classification of exons and introns achieved over 85% accuracy using instantaneous frequency and spectral energy variables.
• Identified key spectral features for distinguishing coding and non-coding regions.

Conclusions:

• Thermodynamic data and time-frequency analysis provide a robust method for pre-mRNA sequence analysis.
• This approach enhances the accuracy of gene localization and annotation in bioinformatics.
• The identified spectral variables are effective discriminators for coding and non-coding regions.