International responses to a single or restricted variety of DNA damage inducers in model systems. Those research could recognize known and novel signalling routes and highlight their important players. These are in particular precious for supplying a much better understanding of drug mechanisms of action, but can also assist identifying possible new drug targets and biomarkers. In the future, potent proteomics technologies could be a precious source for network medicine approaches, which base biomarkers and drug targets on a network of events (protein signature), rather than a single marker or target [96]. Pioneering studies, like mid-level resolution phosphorylation analyses by the Yaffe lab, could predict sensitivity to DNA damage-inducing drugs in breast cancer cells [97]. Initial efforts have explored the predictive power of CCT367766 Formula large-scale phosphoproteomics datasets in the study of signalling pathways in model organisms and drug sensitivity in cancer cells [98,99]. Nonetheless, predictive modelling usually calls for a high-resolving energy of time-points, high reproducibility and high coverage, in order to not miss vital data points. Proteomics analyses are now on an excellent technique to attain the speed, sensitivity and reproducibility that can permit designing
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