Optimization of experimental designs for biological rhythm discovery.

Equally spaced temporal sampling is the standard protocol for the study of biological rhythms. These equispaced designs perform well when calibrated to an oscillator's period, yet can introduce systematic biases when applied to rhythms of unknown periodicity. Here, we investigate how optimizing the timing of measurements can improve rhythm detection across a range of experimental settings. When the period of a rhythm is known, we prove that equispaced designs provide optimal statistical power. In studies targeting specific sets of candidate rhythms, we construct optimal alternatives to equispaced designs to simultaneously maximize power at all frequencies under consideration. For studies investigating continuous period ranges, we show numerically how blindspots near the Nyquist rate can be resolved through timing optimization. Our computational methods are available through our PowerCHORD library. Our findings across all experimental contexts suggest that timing optimization is an effective yet under-explored tool for improving biological rhythm discovery.