Translational and post-translational control mechanisms in the cell result in widely observable differences between measured gene transcription and protein abundances. Herein, protein complexes are among the most tightly controlled entities by selective degradation of their individual proteins. They furthermore act as control hubs that regulate highly important processes in the cell and exhibit a high functional diversity due to their ability to change their composition and their structure. To better understand and predict these functional states, extensive characterization of complex composition, behavior, and abundance is necessary. Mass spectrometry provides an unbiased approach to directly determine protein abundances across cell populations and thus to profile a comprehensive abundance map of proteins. We investigated the behavior of protein subunits in known complexes by comparing their abundance profiles across up to 140 cell types available in ProteomicsDB. After thorough assessment of different randomization methods and statistical scoring algorithms, we developed a computational tool to quantify the significance of concurrent profiles within a complex, therefore providing insights into the conservation of their composition across human cell types. We identified the intrinsic structures in complex behavior that allow to determine which proteins orchestrate complex function. This analysis can be extended to investigate common profiles within arbitrary protein groups. With the CoExpresso web service, we offer a potent scoring scheme to assess proteins for their co-regulation and thereby offer insight into their potential for forming functional groups like protein complexes. CoExpresso can be accessed through http://computproteomics/Apps/CoExpresso. Source code and R scripts for database generation are available at https://bitbucket.org/veitveit/coexpresso
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