Computer Science and Engineering, Department of


Date of this Version



MATEC Web of Conferences 76, 04047 (2016)


© The Authors

Open access

DOI: 10.1051/matecconf/20167604047


Instead of being uniform in each branch of the biological evolutionary tree, the speed of evolution, measured in the number of mutations over a fixed number of years, seems to be much faster or much slower than average in some branches of the evolutionary tree. This paper describes an evolutionary trend discovery algorithm that uses cubic spline interpolation for various branches of the evolutionary tree. As shown in an example, within the vertebrate evolutionary tree, human evolution seems to be currently speeding up while the evolution of chickens is slowing down. The new algorithm can automatically identify those branches and times when something unusual has taken place, aiding data analytics of evolutionary data.