The immune system is an intricate network of cells, proteins, and signaling pathways that coordinate protective responses and, when dysregulated, drive immune−related diseases. Understanding this complexity increasingly relies on systems−based mathematical and computational approaches, which integrate multi−omics data, mechanistic models, and artificial intelligence to reveal the emergent behavior of immune networks. In this mini−review, we discuss the central methodological pillars of systems immunology, including Network Pharmacology, artificial intelligence, and quantitative systems pharmacology. We highlight illustrative applications spanning autoimmune, inflammatory, and infectious diseases, and describe how these methods are used to identify biomarkers, optimize therapies, and guide drug discovery. Finally, we examine current challenges and future directions, including data quality, model validation, and regulatory considerations, which must be addressed to translate systems immunology into clinical impact. This integrated perspective aims to guide both method developers and translational researchers, emphasizing the growing role of computational modeling in next−generation immunology and therapeutic innovation.
Systems immunology: When systems biology meets immunology
L. Alfonso-González,Francisco J. Fernández,M. Vega
Published 2025 in Frontiers in Immunology
ABSTRACT
PUBLICATION RECORD
- Publication year
2025
- Venue
Frontiers in Immunology
- Publication date
2025-09-05
- Fields of study
Biology, Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
Showing 1-64 of 64 references · Page 1 of 1
CITED BY
Showing 1-5 of 5 citing papers · Page 1 of 1