Computational Molecular Biology 2025, Vol.15, No.3, 122-130 http://bioscipublisher.com/index.php/cmb 128 brought about when we review this research in the near future: more rare diseases have been cracked and more patients have been cured, and our platform is an important driver of this. This will be the best reward for our work. Figure 2 The pathoproteomic profile of multi-system changes in Duchenne muscular dystrophy. The diagram outlines the complexity of body-wide alterations due to dystrophin deficiency and illustrates how the systematic application of a comprehensive interproteomic profiling approach could help us better understand the multi-system dysfunction in dystrophinopathy (Adopted from Dowling et al., 2024) Acknowledgments The authors extend sincere thanks to two anonymous peer reviewers for their invaluable feedback on the manuscript. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Ali S., Li Q., and Agrawal P., 2025, Implementation of multi-omics in diagnosis of pediatric rare diseases, Pediatric Research, 97(4): 1337-1344. https://doi.org/10.1038/s41390-024-03728-w Braconi D., Bernardini G., Spiga O., and Santucci A., 2021, Leveraging proteomics in orphan disease research: pitfalls and potential, Expert Review of Proteomics, 18(4): 315-327. https://doi.org/10.1080/14789450.2025.2468300 Casas-Alba D., Hoenicka J., Vilanova-Adell A., Vega-Hanna L., Pijuan J., and Palau F., 2022, Diagnostic strategies in patients with undiagnosed and rare diseases, Journal of Translational Genetics and Genomics, 6(3): 322-332. https://doi.org/10.20517/jtgg.2022.03 Denton N., Molloy M., Charleston S., Lipset C.H., Hirsch J., Mulberg A., Howard P., and Marsh E., 2021, Data silos are undermining drug development and failing rare disease patients, Orphanet Journal of Rare Diseases, 16(1): 161. https://doi.org/10.1186/s13023-021-01806-4
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