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Refined Buneman Trees

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The theory of evolution has also become a cornerstone in philosophy and<br />

modern thinking, to a point where it is almost religious. The phrase survival of<br />

the fittest is the guideline for businesses in the capitalist economy, and playing<br />

God through genetic experiments is one of the most popular scenarios in modern<br />

science fiction.<br />

In this work we shall look at a specific method for inferring evolutionary<br />

history from a set of species, the refined <strong>Buneman</strong> tree algorithm.<br />

1.1 Document structure<br />

This work is organized into three major parts.<br />

Part 1 Overview of Evolutionary <strong>Trees</strong><br />

In the first part we look at evolutionary trees, their applications and some<br />

of the most important tree reconstruction methods and method classes.<br />

We introduce evolutionary principles and mechanisms, and establish how<br />

these may be modelled mathematically.<br />

Part 2 Implementing <strong>Refined</strong> <strong>Buneman</strong> <strong>Trees</strong><br />

In this part we will concern ourselves with the implementation of the<br />

refined <strong>Buneman</strong> tree algorithms described in [BFÖ+ 03]. This algorithm<br />

is the first algorithm that runs in time O(n 3 )andspaceO(n 2 )—the<br />

previous best algorithm would use time O(n 5 )andspaceO(n 4 ). This<br />

implementation is the first of its kind and the first that is practical to<br />

run on larger scale data sets. We will also see how the implementation is<br />

integrated into the widely used JSplits tree visualizing tool.<br />

Part 3 Tests and Experiments<br />

In this part we test the implementation of the refined <strong>Buneman</strong> tree algorithm<br />

to see if it performs as specified, and we also perform experiments<br />

that demonstrate the applicability of the method, relating it to the well<br />

known Neighbor-Joining method.<br />

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