Paper Type

ERF

Abstract

Integration of data from the National Center for Biotechnology Information (NCBI) and the Gene Ontology (GO) Consortium is crucial for functional genomics research, yet challenges like inconsistent identifiers and limited batch processing hinder accessibility. This emergent research presents a high-level workflow for cross-referencing gene data between NCBI and GO to enable functional enrichment analysis, using Escherichia coli stress response genes as a case study. The pipeline involves gene identification in NCBI, API-based data retrieval, GO ID extraction, and enrichment analysis via tools like PANTHER. We discuss technical barriers, research applications, and propose future improvements for user-friendly information systems. This work highlights opportunities for IS research in enhancing bioinformatics tools for broader adoption.

Paper Number

1936

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Aug 15th, 12:00 AM

Cross-Database Integration for Functional Genomics: A Workflow for NCBI and Gene Ontology

Integration of data from the National Center for Biotechnology Information (NCBI) and the Gene Ontology (GO) Consortium is crucial for functional genomics research, yet challenges like inconsistent identifiers and limited batch processing hinder accessibility. This emergent research presents a high-level workflow for cross-referencing gene data between NCBI and GO to enable functional enrichment analysis, using Escherichia coli stress response genes as a case study. The pipeline involves gene identification in NCBI, API-based data retrieval, GO ID extraction, and enrichment analysis via tools like PANTHER. We discuss technical barriers, research applications, and propose future improvements for user-friendly information systems. This work highlights opportunities for IS research in enhancing bioinformatics tools for broader adoption.

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