Large-scale multimodal data on patient health is an important factor in the development of personalized medicine.

Biomedical Big data is inherently versatile. However, generation, storage, and analysis processes can incorporate inaccuracies that occur when the different structure–function relationships of the intrinsically disordered proteins and the post-translational modifications of proteins, used without a spatiotemporal interpretation, generate inaccurate interpretations in hub genes’ protein–protein interaction networks.

We encourage the biomedical community to search for a solution that can rectify data retrospectively, as pitfalls and flaws must be avoided when generating clinical decisions in personalized medicine..