Here, we investigated the systemic alterations of human mt protein functional network under normal and dysfunctional mt states through a data-integrative computational biology approach and quantitative proteomic analysis. Specifically, a systematic data-integrative analysis was devised to evaluate the reliability of mt proteomics data and cluster the identified proteins into the modules of mt protein functional network. Our results revealed that human mt proteins comprise specific network modules to control unique biological processes in cells exposed to dysfunctional mt states. Furthermore, network clustering suggests that cells respond to pathological conditions by modulating the coordinated expression and transport of mitochondrial proteins. We believe that our results may provide critical information to gain better understanding of mitochondria function in the cell.