Using Huffman coding method to visualize and analyze DNA sequences

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• DNA sequence data presents challenges in representation and quantitative analysis.
• Existing methods may suffer from information loss or degeneracy during data transfer.
• Accurate quantitative characterization is crucial for comparative genomics and evolutionary studies.

Purpose of the Study:

• To propose a novel graphical representation for DNA sequences based on Huffman coding.
• To ensure information integrity and avoid degeneracy in DNA sequence representation.
• To introduce a multicomponent vector for quantitative DNA sequence characterization.

Main Methods:

• Utilizing Huffman coding to create a new graphical representation of DNA sequences.
• Deriving multicomponent vectors from the graphical representation.
• Analyzing similarities and dissimilarities using the proposed scheme.

Main Results:

• The proposed graphical representation avoids degeneracy and information loss.
• The multicomponent vector effectively quantifies DNA sequence characteristics.
• The scheme demonstrated utility in analyzing β-globin and ND6 protein coding sequences across species.

Conclusions:

• The Huffman coding-based graphical representation offers an effective method for DNA sequence analysis.
• The developed vectorization technique provides a robust tool for quantitative sequence comparison.
• This approach enhances the study of genetic relationships and evolutionary patterns.