Data Structures to Represent a Set of k -long DNA Sequences.

Area of Science:

• Bioinformatics
• Computational Biology
• String Algorithms

Background:

• Biological sequencing data analysis heavily relies on string algorithms.
• K-mers (short fixed-length strings) are fundamental units in many sequencing data applications.
• Efficiently storing and querying k-mer sets is a shared challenge across diverse approaches.

Purpose of the Study:

• To provide a unified presentation and comparison of data structures for k-mer set representation.
• To serve as a resource for researchers specializing in k-mer analysis.
• To make the field of k-mer data structures more accessible to a broader research audience.

Main Methods:

• Literature review and synthesis of existing data structures for k-mer sets.
• Comparative analysis of different representation approaches.
• Categorization and unified presentation of specialized k-mer storage and querying techniques.

Main Results:

• Identification of diverse, specialized data structures developed over the past decade for k-mer sets.
• A comparative overview highlighting the unique features and applications of these structures.
• A unified framework for understanding and evaluating k-mer data structures.

Conclusions:

• Specialized data structures are essential for efficient k-mer set management in bioinformatics.
• This survey consolidates knowledge, aiding researchers in selecting appropriate methods.
• The presented comparison facilitates further development and accessibility in k-mer analysis.