A pattern matching approach for the estimation of alignment between any two given DNA sequences.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Pairwise alignment is crucial for determining DNA sequence similarity and inferring proteomic identity.
• Existing alignment methods can be computationally intensive, necessitating more efficient approaches.

Purpose of the Study:

• To propose a novel block-based semi-global alignment scheme for evaluating DNA sequence similarity.
• To introduce a pattern matching approach for assessing proteomic identity based on DNA sequences.

Main Methods:

• DNA sequences were divided into equal-length blocks for semi-global alignment.
• A pattern matching approach utilized four essential DNA versions of amino acids.
• Percentage of Similarity (POS) and amino acid count ratios were used as evaluation metrics.

Main Results:

• The block-based semi-global alignment scheme effectively determined DNA sequence similarity.
• Higher POS values and successful pattern matching correlated with increased sequence similarity.
• An optimal block size was identified based on POS and amino acid counts.

Conclusions:

• The proposed block-based semi-global alignment and pattern matching approach offers an efficient method for DNA sequence comparison.
• This method aids in evaluating proteomic identity and understanding DNA sequence relationships.
• The findings provide insights into optimizing alignment strategies for genomic data analysis.