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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Towards a unified framework for single-cell -omics-based disease prediction through AI.

Matteo Barberis1,2, Jinkun Xie1,2

  • 1Molecular Systems Biology, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.

Clinical and Translational Medicine
|April 2, 2025
PubMed
Summary
This summary is machine-generated.

Single-cell omics combined with artificial intelligence (AI) can predict diseases and stages. This framework, scDisPreAI, identifies key biomarkers for tailored treatments and drug discovery.

Keywords:
Clinical Decision Assistantartificial intelligencedeep learningdisease predictiondrug repurposingmachine learningmedicinesingle‐cell ‐omics

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Area of Science:

  • Biotechnology
  • Bioinformatics
  • Computational Biology

Background:

  • Single-cell omics reveals cellular heterogeneity crucial for understanding health and disease.
  • Artificial intelligence (AI) offers advanced pattern recognition and predictive modeling for clinical applications.

Discussion:

  • The proposed scDisPreAI framework integrates single-cell omics data using AI for disease and stage prediction.
  • It establishes a standardized database and employs rigorous preprocessing for reliable biological insights.
  • Machine learning and deep learning models are trained for multi-task classification, identifying disease identity and stage.

Key Insights:

  • Interpretability techniques (SHAP, attention weights) identify influential genes, serving as potential biomarkers.
  • Biomarkers may be shared across different diseases or disease stages, offering broad therapeutic potential.
  • scDisPreAI consolidates prediction with biomarker discovery for clinical decision support.

Outlook:

  • Future directions include integrating multi-omics data and standardizing protocols for broader applicability.
  • Prospective clinical validation is essential to realize the full potential of single-cell AI in precision medicine.
  • The framework aims to guide tailored treatments and identify therapeutic targets for drug repurposing.