GENEVIC: GENetic data exploration and visualization via intelli- gent interactive console.
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