In the architectural approach to the study of plants, a major issue is to analyse branching and axillary flowering patterns. Due to the structured expression of the branching process and the noisy character of the observed patterns, we propose an analysis framework which is both structural and probabilistic. Data take the form of sequences which naturally represent the underlying structural information of branching and axillary flowering patterns and allow the application of a large number of methods ranging from exploratory analysis to stochastic modeling. The primary aim of the proposed analysis methods is to reveal patterns not directly apparent in the data, and thus to deepen our biological understanding of the underlying mechanisms that control the branching and the axillary flowering of plants over time and space. The proposed approach is illustrated using a set of examples corresponding to different plant species and different biological or agronomic objectives.