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Updated: May 24, 2026

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

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Published on: September 20, 2024

AI in multi-omics analysis in obstructive lung diseases.

Paramita Roy¹, Sudipto Saha¹

¹Department of Biological Sciences, Bose Institute, Kolkata, India.

Progress in Molecular Biology and Translational Science

|May 22, 2026

Summary

This summary is machine-generated.

Obstructive lung diseases (OLDs) like asthma and COPD are rising. Multi-omics integration with AI offers new insights into host-microbiome interactions for better disease classification and risk assessment.

Keywords:

AI/ML COPD Obstructive lung diseases asthma multi-omics integration

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Published on: January 7, 2019

Area of Science:

Pulmonary Medicine
Bioinformatics
Genomics

Background:

Obstructive lung diseases (OLDs), including asthma, COPD, and bronchiectasis, exhibit increasing global prevalence.
Current treatments for OLDs are limited, primarily relying on antibiotics and steroids.
Understanding host-microbiome interactions is crucial for developing novel therapeutic strategies.

Purpose of the Study:

To review multi-omics integration approaches for studying OLDs.
To highlight the application of AI and statistical methods in analyzing multi-omics data for OLDs.
To discuss the insights gained from multi-omics studies in asthma, COPD, and bronchiectasis.

Main Methods:

Review of multi-omics integration studies in obstructive lung diseases.
Analysis of artificial intelligence (AI) and statistical approaches for multi-omics data integration.
Examination of host, microbiome, and host-microbiome interactions in OLDs.

Main Results:

Multi-omics integration provides deeper insights into OLDs.
AI-driven analyses facilitate the integration of complex multi-omics datasets.
Studies have focused on disease subtype classification, risk assessment, and genetic associations.

Conclusions:

Multi-omics integration is a powerful approach for understanding OLDs.
AI enhances the analysis of multi-omics data for improved disease insights.
Further research in this area holds promise for advancing OLDs management.