Clinical Artificial Intelligence for High-Resolution Single-Cell Analysis: Opportunities and Challenges for Therapeutic Interpretation

Résumé fourni par la source

Cells are the basic structural and functional unit of life, and the ability to study and explore genotypic and phenotypic characteristics is important to understand the complex biological mechanisms happening within a cell. Cells in different tissues exhibit enormous heterogeneity that gives rise to variations in the function of cells during health and disease. Over the last decade, single-cell analysis has gained huge attention, particularly after the emergence of AI-based algorithms. The 10x Genomics and microfluidic technologies help to analyse transcriptomes on a cell-by-cell basis. Single-cell ChIP- sequncing technologies play a very important role in mapping cellular diversity, histone modifications, and protein-DNA interactions. In this short communication, we have discussed the advanced single-cell multi-omics methods, AI-driven technologies, and their applications. We have highlighted how single-cell analysis, such as NGS and other computational methods, can change the landscape of healthcare and its impact on the fundamental translational research for personalized medicine. This article also discusses the existing challenges, such as regulatory aspects and issues related to data privacy, safety, and possible biases.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.