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GeneWhisperer: Enhancing manual genome annotation with large language models

Xiaomei LiiD, Alex WhaniD, Meredith McNeiliD, Samuel C. AndrewiD, Xiang DaiiD, Madeline Fechner, Cécile L. ParisiD, Rad Suchecki

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Abstract

Genome annotation is critical for understanding functional elements within genomes. Manual curation is a common practice for identifying the functions of genes, particularly those missed by automated annotation pipelines. However, this process is notoriously labour-intensive and time-consuming. In response to these challenges, we present GeneWhisperer, an innovative assistant system designed to facilitate the manual gene functional annotation process. Utilizing a large language model (LLM) agent, GeneWhisperer provides users access to tools appropriate for specific curation tasks in genome annotation. Featuring a conversational interface, GeneWhisperer fosters effective collaboration between human experts and AI. By synergizing the capabilities of AI with human expertise, GeneWhisperer offers a promising approach to advancing our understanding of gene functions and streamlining the gene annotation process.

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Calvin Boyce, Clara Pereira, Gyeong Dae Kim+1 more·bioRxiv·Aug 6, 2025· 1 citations