Minimizing phylogenetic number to find good evolutionary trees

Minimizing Phylogenetic Number to find Good Evolutionary Trees

Inferring phylogenetic trees is a fundamental problem in computational biology. We present a new objective criterion, the phylogenetic number, for evaluating evolutionary trees for species deened by biomolecular sequences or other qualitative characters. The phylogenetic number of a tree T is the maximum number of times that any given character state arises in T. By contrast, the classical pars...

Evolutionary models of phylogenetic trees.

The most widely used evolutionary model for phylogenetic trees is the equal-rates Markov (ERM) model. A problem is that the ERM model predicts less imbalance than observed for trees inferred from real data; in fact, the observed imbalance tends to fall between the values predicted by the ERM model and those predicted by the proportional-to-distinguishable-arrangements (PDA) model. Here, a conti...

Using Magma to find good xorshift random number generators

Good random number generators are (not so) easy to find

Every random number generator has its advantages and deficiencies. There are no `̀ safe'' generators. The practitioner's problem is how to decide which random number generator will suit his needs best. In this paper, we will discuss criteria for good random number generators: theoretical support, empirical evidence and practical aspects. We will study several recent algorithms that perform bette...

Inferring Phylogenetic Trees Using Evolutionary Algorithms

We consider the problem of estimating the evolutionary history of a collection of organisms in terms of a phylogenetic tree. This is a hard combinatorial optimization problem for which different EA approaches are proposed and evaluated. Using two problem instances of different sizes, it is shown that an EA that directly encodes trees and uses ad-hoc operators performs better than several decode...