Biobtree: A tool to search, map and visualize bioinformatics identifiers and special keywords

Area of Science:

• Bioinformatics
• Computational Biology
• Data Science

Background:

• Bioinformatics datasets are inherently interconnected, necessitating robust methods for searching, mapping, and visualizing these relationships.
• Current approaches often rely on manual or programmatic methods using gene symbols or identifiers, which become challenging with increasing data volumes and emerging tools.

Purpose of the Study:

• To introduce Biobtree, a novel bioinformatics tool designed to address the challenges of managing and querying interconnected bioinformatics data.
• To provide an efficient solution for fetching, indexing, and relating identifiers and keywords across diverse datasets.

Main Methods:

• Biobtree utilizes a B+ tree data structure for efficient indexing and storage of identifiers and associated keywords.
• The tool supports fetching data from supported datasets and optionally user-defined datasets.
• It offers a single executable file with no installation or dependencies, simplifying deployment.

Main Results:

• Biobtree effectively indexes identifiers and related keywords, enabling efficient search and mapping.
• The tool is capable of handling billions of identifiers within a single, uniform database.
• It provides a web interface and web services for accessibility and integration.

Conclusions:

• Biobtree offers a scalable and efficient solution for managing complex relationships within bioinformatics datasets.
• Its design emphasizes ease of maintenance, extensibility, and accessibility, making it a valuable resource for the bioinformatics community.
• The tool is readily available for download, promoting adoption and further development.