FatPlants 2.0: an AI-powered platform integrating plant lipid genes, pathways, and literature

Plant lipid research depends on accessible databases that connect genes, pathways, and prior literature. However, currently available resources are fragmented, species-limited, and lack AI-powered interfaces for integrated querying. FatPlants 2.0 addresses these issues by integrating ARALIP, PlantFADB, and new Cuphea/Pennycress experimental data into a unified platform with 14 000 genes/proteins, 110 pathways across 5 species, and 57 000+ curated publications. The platform features LipidBot, an AI agent enabling natural language queries via graph-based pathway search and retrieval-augmented generation-powered literature retrieval. Users query complex relationships conversationally and receive answers with traceable citations. The graph database models 100+ biological pathways as queryable networks with large language model-guided Cypher generation. By evaluating more than 1000 curated questions, LipidBot achieved 95% accuracy on pathway queries and 92% recall in literature retrieval using optimized embeddings. The tool demonstrated robust performance across factual, numerical, and multi-hop queries on curated benchmarks. FatPlants 2.0 accelerates research by reducing the time spent on literature reviews. Database and AI agent freely available at https://fatplants.net with bulk downloads and quarterly updates.