ArticleDatabase : the journal of biological databases and curation2026
Developing a web-based platform for Eragrostis tef resource management and analysis.
Article in Database : the journal of biological databases and curation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
Developing a web-based platform is beneficial for data accessibility, centralization, security, management, and scalability. Eragrostis tef is an indigenous cereal crop in Ethiopia that currently lacks specialized or unified web-based platforms compared with major crops. This gap hinders genomic research, crop improvement programs, and the efficient utilization of tef genetic resources. Consequently, challenges include data fragmentation and the absence of a centralized database for accessing and managing tef-related data. In this study, a centralized platform called the Tef Database (TefDB) was developed. The platform integrates 77 795 tef-specific biological records, including 1 372 literature entries, 6 144 genome-related records, 66 455 gene models, 3 447 protein sequences, and 377 chemical/pathway entries. Advanced features were included along with the platform's interactive, visualization, responsive, searchable and filterable, downloadable, and analysis tools. The platform was built using modern web technologies: React.js for the frontend, Django and Python for backend processing, and PostgreSQL for data management. The Design Science Research (DSR) methodology guided development, incorporating iterative input from potential users. The platform's usability, performance, and functionality were validated through testing. TefDB offers bioinformatics analysis through natively embedded tools (BLAST and JBrowse 2) and externally linked tools (Primer3Plus and Clustal Omega) that open in new browser tabs. This integration reduces workflow fragmentation, allowing users to move seamlessly from data retrieval to analysis without exporting datasets to external platforms. Future work should focus on platform upgrades, data updates and integration, integration of local tef variety data (including SNPs and VCFs), advanced analytical modules, and collaborative user features.
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