PubMed · 2026-05-23
A team of plant scientists reflects on ten years of building TBtools, a free software that lets researchers explore massive gene and molecular datasets without needing to write code. They distill eight design lessons and sketch a blueprint for the next generation of tools — ones powered by AI assistance and cloud computing — to help biologists turn data mountains into actual discoveries faster.
TBtools achieved broad adoption over a decade by providing interactive, low-barrier access to common plant omics tasks — narrowing the skills gap between experimental biologists and increasingly complex datasets.
The authors distilled eight actionable design recommendations from this case study that explain why certain locally-run tools succeed where others are ignored.
Four pillars are proposed for next-generation tools: project-level data management, reproducible workflow construction, elastic remote computing, and AI-assisted navigation and automation.