As a vertebrate cardiovascular model, the zebrafish heart has been used extensively in physiology research to study cardiac development and human cardiac disease. Optical mapping techniques provide an effective approach to record action potential propagation in the zebrafish heart. However, manual analysis of functional time series recorded from optical mapping can be laborious and time consuming. In this paper, a novel pipeline is proposed to assist physiologists in identifying the sinoatrial node (SAN) in zebrafish heart based on functional time series. First, the original optical mapping data are enhanced and averaged. Next, the heart is divided into small regions, and representative average time series are calculated. A 'discretization of derivative' (DoD) process is performed to model physiological similarity between signals. Finally, grouping is done on the DoD transformed representation, which is found to produce physiologically meaningful classification for SAN identification.