Application of process mining approach to the developmental process of the roundworm C. elegans

Abstract

Process mining is an analytical approach which stems from and converges on data science and process modelling. Initially incepted to support business process management, however process mining approach is universal and applicable to other fields. It was already discerned that process mining techniques share similarities with such used in bioinformatics and that the emerging process mining discipline can benefit from applying techniques developed in computational biology [1]. Herein however, we demonstrate the reverse: that process mining can be applied for the study biological processes. As process mining operates on event logs in order to analyze a particular biological process it is necessary to transform the information for a sequence of biological events into an event log. For this study we applied process mining techniques to a developmental dataset from the lineage-resolved molecular atlas of the round worm C. elegans [2]. The single-cell temporal gene expression data was transformed into event log and analyzed with process mining tools. We show that application of process mining to biological processes is feasible, yet the presentation of the results with current tools is not suitable for the high information content of the particular biological process and this hampers further extraction of knowledge. We conclude that the application of process mining to biological processes would be beneficial for both fields.