An efficient similarity search based on indexing in large DNA databases

Area of Science:

• Bioinformatics
• Computational Biology
• Genomic Data Analysis

Background:

• Index-based search algorithms are crucial for efficient genomic data retrieval.
• Constructing effective indices is key to computing similarities between DNA sequences.

Purpose of the Study:

• To propose an efficient query processing method for genomic search.
• To develop an index construction technique that uses minimal storage and enhances search speed.

Main Methods:

• Partitioning DNA sequences into equal-length windows.
• Selecting candidate subsequences using Hamming distance to the query sequence.
• Transforming subsequences into a multidimensional vector space by indexing character frequencies and positional information.

Main Results:

• The proposed algorithm demonstrates faster runtimes compared to other heuristic index-based algorithms.
• The algorithm achieves accuracy comparable to existing heuristic methods.

Conclusions:

• The developed index construction method is efficient for processing queries in DNA sequence databases.
• This approach offers a promising solution for rapid and accurate similarity searches in large genomic datasets.