[Fast comparison of groups of sequences using computers]

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Identifying identical fragments in biological sequences is crucial for various analyses.
• Existing methods may lack efficiency in handling large datasets of amino acid and nucleotide sequences.

Purpose of the Study:

• To describe a novel library of programs designed for efficient searching of identical fragments.
• To present a method for finding conserved regions within biological sequence data.

Main Methods:

• Development of a program library for sequence analysis.
• Creation of a keyword table to index short sequence motifs.
• Algorithmic approach to identify longer coinciding sequence fragments based on the keyword table.

Main Results:

• The program library effectively identifies identical fragments in amino acid and nucleotide sequences.
• The keyword table approach facilitates the discovery of longer matching sequence sections.
• Demonstrated efficiency in locating conserved regions within sequence groups.

Conclusions:

• The described program library offers an efficient tool for identifying identical sequence fragments.
• The keyword-based strategy enhances the detection of conserved regions in biological data.
• This approach supports large-scale sequence analysis in bioinformatics and related fields.