E. Baek, Ho-Jong Ju, Jiwan Seo, Ju-Yeon Yoon
2026.2.1Plant Pathology Journal
tlooto Summary
Using vibe coding, a generative AI assisted method that enables non-programmers to process and visualize data efficiently allowed rapid organization of large datasets and real-time utilization of newly deposited GenBank entries.
Abstract
Understanding and predicting epidemiological trends of plant viruses is essential for sustaining crop productivity and control strategies. The National Center for Biotechnology Information (NCBI) GenBank provides nucleotide sequences with metadata such as date, location, and host, offering valuable resources for research. However, GenBank lacks automated tools for visualizing temporal and spatial patterns. To address this limitation, we applied a vibe coding approach, a generative AI assisted method that enables non-programmers to process and visualize data efficiently. As a case study, we analyzed pepper (Capsicum spp.), a major East and Southeast Asian crop threatened by emerging viruses. Using vibe coding, we visualized reporting trends by country and year and mapped sequence variation and conserved regions of pepper-infecting viruses. This approach allowed rapid organization of large datasets and real-time utilization of newly deposited GenBank entries. NCBI-based plant virus analysis system provides automated analysis and visualization and is accessible at https://plantvirus-viewer.duckdns.org/.
Citation format
BAEK, E., et al. A vibe coding workflow for AI-Assisted analysis and visualization of genbank records of pepper infecting viruses. Plant Pathology Journal, 2026, 42(1): 103–108.