Tropical Data Science
This is an incremental survey for researchers in phylogenomics, focusing on applying existing methods to new data without solving a new problem.
The paper addresses the challenge of analyzing phylogenetic tree data in non-Euclidean spaces by surveying machine learning models that use tropical geometry, but it does not provide specific results or numbers.
Phylogenomics is a new field which applies to tools in phylogenetics to genome data. Due to a new technology and increasing amount of data, we face new challenges to analyze them over a space of phylogenetic trees. Because a space of phylogenetic trees with a fixed set of labels on leaves is not Euclidean, we cannot simply apply tools in data science. In this paper we survey some new developments of machine learning models using tropical geometry to analyze a set of phylogenetic trees over a tree space.