bioRxivBioinformaticsPreprint
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
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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