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GENEVIC: GENetic data exploration and visualization via intelli- gent interactive console.
Nath, Anindita; Mwesigwa, Savannah; Dai, Yulin; Jiang, Xiaoqian; Zhao, Zhong-Ming.
Afiliación
  • Nath A; Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
  • Mwesigwa S; Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
  • Dai Y; Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
  • Jiang X; Department of Health Data Science and Artificial Intelligence, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, TX 77030, USA.
  • Zhao ZM; Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Bioinformatics ; 2024 Aug 08.
Article en En | MEDLINE | ID: mdl-39115390
ABSTRACT

SUMMARY:

The vast generation of genetic data poses a significant challenge in efficiently uncovering valuable knowledge. Introducing GENEVIC, an AI-driven chat framework that tackles this challenge by bridging the gap between genetic data generation and biomedical knowledge discovery. Leveraging generative AI, notably ChatGPT, it serves as a biologist's 'copilot'. It automates the analysis, retrieval, and visualization of customized domain-specific genetic information, and integrates functionalities to generate protein interaction networks, enrich gene sets, and search scientific literature from PubMed, Google Scholar, and arXiv, making it a comprehensive tool for biomedical research. In its pilot phase, GENEVIC is assessed using a curated database that ranks genetic variants associated with Alzheimer's disease, schizophrenia, and cognition, based on their effect weights from the Polygenic Score (PGS) Catalog, thus enabling researchers to prioritize genetic variants in complex diseases. GENEVIC's operation is user-friendly, accessible without any specialized training, secured by Azure OpenAI's HIPAA-compliant infrastructure, and evaluated for its efficacy through real-time query testing. As a prototype, GENEVIC is set to advance genetic research, enabling informed biomedical decisions. AVAILABILITY AND IMPLEMENTATION GENEVIC is publicly accessible at https//genevic- anath2024.streamlit.app. The underlying code is open-source and available via GitHub at https//github.com/bsml320/GENEVIC.git (also at https//github.com/anath2110/GENEVIC.git). SUPPLEMENTARY INFORMATION Available at Bioinformatics online and at https//github.com/bsml320/GENEVIC_Supplementary.git (also at https//github.com/anath2110/GENEVIC_Supplementary.git).

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos