In recent years, we developed a framework to study fluctuating signals generated by complex systems, specifically, for biological systems. We have demonstrated that it is possible to gain significant understanding of a complex biological system via studying its spontaneous fluctuations in time. This framework has tremendous utility for biomedical problems. However, a major technical challenge is that those fluctuating time series generated by biological systems are often nonlinear and nonstationary, and thus, require novel analysis techniques that can handle nonstationary trends and quantify instantaneous frequencies.