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Non-smooth or even abrupt state changes exist during many biological processes, e.g., cell differentiation process, proliferation process, or even disease deterioration process.Such dynamics generally signal the emergence of critical transition phenomena, which result in drastic changes in system states or eventually qualitative changes in phenotypes.Hence, it is of great importance to detect such transitions, the critical drug-targets, and further reveal their molecular mechanism at network level.Here, we describe the recent advances on dynamical network biomarkers (DNBs) as well as the related theoretical foundation, which can identify not only early signals of the critical transitions but also their leading networks, which are critical drug targets and drive the whole system to initiate such transitions.For demonstrating the effectiveness of this novel approach, examples for complex diseases are also provided to detect pre-disease stage and their drug targets, for which traditional methods failed.