Bioinfo Chem
System biology and Infochemistry | Online ISSN 3071-4826
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Volume 5 Number 1 2023
REVIEWS (Open Access)
Network-Based Systems Biology for Disease Pathway Modeling: Multi-Omics Integration and Computational Analysis
Ramji Gupta 1*, Adesh Kolapkar 2*
Bioinfo Chem 5 (1) 1-12 https://doi.org/10.25163/bioinformatics.5110720
Submitted: 26 April 2023 Revised: 12 June 2023 Accepted: 22 June 2023 Published: 24 June 2023
Abstract
Systems biology is increasingly transforming disease pathway modeling by moving beyond reductionist approaches toward network-based and integrative frameworks. Traditional methods that focus on individual genes or pathways often fail to capture the complexity of disease mechanisms, particularly in multifactorial conditions. This narrative review examines how systems biology approaches—combining multi-omics integration, network analysis, and computational modeling—enable a more comprehensive understanding of disease pathways. Recent advances demonstrate that integrating genomic, transcriptomic, proteomic, and metabolomic data allows reconstruction of disease networks with greater biological resolution. Computational approaches, including Bayesian networks, differential equation modeling, and pathway impact analysis, provide dynamic and predictive insights into disease mechanisms. These methods highlight how biological function emerges from interconnected systems rather than isolated components. The concept of biological robustness is also explored, emphasizing its dual role in maintaining physiological stability while contributing to disease persistence in complex disorders such as cancer and neurodegeneration. Despite these advances, challenges remain, including data heterogeneity, limited model interpretability, and the gap between computational predictions and clinical validation. Overall, systems biology offers a shift toward predictive, network-based disease modeling. Continued progress will depend on improved data integration, robust validation, and the translation of computational insights into clinical applications.
Keywords: Systems biology; Disease pathway modeling; Multi-omics integration; Network analysis; Computational modeling
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