Deciphering Disease Progression Through Multi-Omics Integration
A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Biology".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 1
Special Issue Editor
2. Department of Biomedical Sciences, University of Padova, Via U. Bassi 58/B, 35131 Padova, Italy
Interests: proteomics; mass spectrometry; cancer proteomics; protein identification; peptidomics; phosphoproteomics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in high-throughput omics technologies are providing unprecedented opportunities to unravel the molecular mechanisms underlying disease onset and progression. Integrating multi-omics data—including genomics, transcriptomics, proteomics, metabolomics, and lipidomics—enables a comprehensive and system-level view of biological regulation, offering new routes for the discovery of diagnostic and prognostic biomarkers as well as potential therapeutic targets.
This Special Issue, “Deciphering Disease Progression through Multi-Omics Integration”, aims to collect cutting-edge studies and reviews that explore the power of multi-omics approaches in understanding complex diseases. We welcome contributions that apply or develop integrative methodologies across omics layers, address challenges in data harmonization and computational modelling, or demonstrate translational relevance in clinical and pre-clinical contexts. Studies focusing on molecular mechanisms, network-based approaches, or advances in technological approaches are also encouraged.
By bringing together experimental and computational perspectives, this Special Issue seeks to highlight how integrative omics can bridge molecular alterations to phenotypic outcomes, ultimately contributing to precision medicine and the identification of new biomarkers for human health and disease.
Dr. Cinzia Franchin
Guest Editor
Manuscript Submission Information
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Keywords
- multi-omics integration
- systems biology
- biomarkers
- disease progression
- precision medicine
- computational modelling
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