- Annual Conference 2014
- About Us
- Apply to CoMPLEX
- For Students
- Students & Alumni
Modelling: Big Data and Society Conference
A new PhD student publication
Dr. David Dale
David’s work during his time in CoMPLEX provides a defence of the claim that likelihood based methods provide a better framework for performing phylogenetic analyses on molecular sequences than do parsimony based methods under the conditions studied. David’s novel work introduced in his thesis includes simulation studies that examine the performance of likelihood based and parsimony based methods at high evolutionary distances. At these distances, many changes accumulate at a single site causing a catastrophic collapse in the performance of the parsimony analysis. In contrast a well understood mathematical theory involving the use of Fisher’s information measure describes the decline in performance of likelihood methods.
Further work by David compared the performance of likelihood based methods and parsimony methods under heterotachous conditions, i.e. conditions under which a single site will alter its rate of evolution relative to other sites. He rebutted a recent claim that parsimony based analyses outperform likelihood. He then introduced a likelihood model and he analyzed its performance.
Finally, he defined likelihood-based methods in terms of rates. He describes a method for turning these rates into a probability distribution describing the number of changes of interest across a phylogeny. He then compared it to the number of changes inferred under a parsimony analysis. When the true model is known, he showed that the counts of changes inferred under a parsimony-based analysis have a low probability of being correct. He argues in his thesis that this accounts for the poor performance of parsimony.
David’s homepage: http://www.ucl.ac.uk/~ucbpdcd/
Page last modified on 23 aug 09 15:17