Harnessing large language models (LLMs) for candidate gene prioritization and selection

Harnessing large language models (LLMs) for candidate gene prioritization and selection

Abstract Background Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for selecting candidate genes, knowledge-driven methods must contend with the challenge o...

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Bibliographic Details
Main Authors: Mohammed Toufiq, Darawan Rinchai, Eleonore Bettacchioli, Basirudeen Syed Ahamed Kabeer, Taushif Khan, Bishesh Subba, Olivia White, Marina Yurieva, Joshy George, Noemie Jourde-Chiche, Laurent Chiche, Karolina Palucka, Damien Chaussabel
Format: Article
Language:English
Published: BMC 2023-10-01
Series:Journal of Translational Medicine
Subjects:
Transcriptomics
Erythroid cells
Feature selection
Large language models
Generative artificial intelligence
Online Access:https://doi.org/10.1186/s12967-023-04576-8

Internet

https://doi.org/10.1186/s12967-023-04576-8

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