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

Abstract

SUMMARY 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.