Prog Mol Biol Transl Sci. 2026;222:165-206. doi: 10.1016/bs.pmbts.2026.01.025. Epub 2026 Mar 2.

ABSTRACT

The reports of obstructive lung diseases (OLDs) like asthma, chronic obstructive pulmonary disease (COPD), and bronchiectasis show increasing global prevalence. The available treatment options for these diseases are limited to antibiotics and steroids. Different multi-omics integration approaches have been applied in studying host, microbiome, and host-microbiome interactions in these diseases to get better insights. Artificial intelligence (AI)-based, as well as statistical and other approaches, are used for multi-omics analyses, specifically the integration of multi-omics data in OLDs. This chapter discusses various aspects of multi-omics integration studies in asthma, COPD, and bronchiectasis. Overall, these studies focused on disease subtype classification, risk assessment, association with genetic factors, and several other aspects.

PMID:42173629 | DOI:10.1016/bs.pmbts.2026.01.025

Prog Mol Biol Transl Sci. 2026;222:143-163. doi: 10.1016/bs.pmbts.2026.03.010. Epub 2026 Apr 10.

ABSTRACT

The reports of lung, breast, colorectal, and prostate cancers show increasing global prevalence. Cancer recurrence and drug resistance are open challenges in these fields. Different multi-omics integration approaches have been applied in cancer type sub-classification and prediction of patient survival and recurrence. Artificial intelligence (AI)-based, as well as statistical and other approaches, are used for multi-omics analyses, specifically for integrating multi-omics data in cancer. This chapter discusses multi-omics resources available for reanalyzing cancer data and for developing AI-based prediction models. Different aspects of multi-omics integration studies of major cancers are also discussed in this chapter. Overall, these studies focused on disease subtype classification, risk assessment, cancer recurrence, survivability, and several other aspects.

PMID:42173628 | DOI:10.1016/bs.pmbts.2026.03.010