Rule-based recommendation system for phylogenetic inference

Abstract

Phylogenetic Inference is the reconstruction of a phylogenetic tree that depicts the evolutionary relationship among a group of taxa. This evolutionary relationship between different groups of species is useful for fields such as medicine, forensics, and drug discovery. With the availability of multiple phylogenetic inference algorithms, it is challenging to select the optimal algorithm for novice users. Moreover, it is essential to compare the accuracy and efficiency of different algorithms for a given dataset. Thus, there is a need for a recommendation system to identify the most appropriate phylogenetic inference algorithm for each dataset. This paper presents a Rule-based recommendation component that suggests users with suitable algorithms for inferencing. The evaluation results show the recommendations suggested by the system are 86.7% relevant and accurate.