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Plant CommunicationsBioinformaticsPeer-reviewed journal article

DeepPGDB: A Novel Paradigm for AI-Guided Interactive Plant Genomic Database

Fangping LiiD, Jiaxuan Chen, Wei LuoiD, Jieying LiuiD, Guodong CheniD, Binyu ShuaiiD, Zhuangwei HouiD, Zhenpeng GaniD, Hongyuan ZhaoiD, Penglin Zhan, Bi CheniD, Zefu WangiD, Haifei HuiD, Shaokui WangiD

PDFDOIPreprint

Abstract

DeepPGDB (https://www.deeppgdb.chat) is the first AI-driven plant genomics database designed to lower technical barriers in multi-omics research by enabling natural language-based data access and analysis. Integrating over 50 high-quality plant genomes, DeepPGDB combines fine-tuned large language models (LLMs) with prompt engineering to interpret user queries, generate standardized bioinformatics commands, and retrieve or visualize genomic data. Key functionalities include sequence retrieval, BLAST alignment, gene localization, expression profiling, and population genetics analysis, all presented via an intuitive conversational interface. A summarization module further enhances biological reasoning, inferring insights such as haplotype differentiation or protein properties. Benchmarking revealed that Deepseek-r1:14b optimized for short pre-prompts delivers high accuracy and speed. By bridging computational and biological expertise, DeepPGDB democratizes genomic research, fostering interdisciplinary collaboration and accelerating discoveries in agriculture and biotechnology.

Citations
3
FWCI
0.90
Field percentile
top 29%

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