COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |

University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Likelihood Maximization on Phylogenic Trees

## Likelihood Maximization on Phylogenic TreesAdd to your list(s) Download to your calendar using vCal - Hauser, R (University of Oxford)
- Friday 19 July 2013, 10:00-10:30
- Seminar Room 1, Newton Institute.
If you have a question about this talk, please contact Mustapha Amrani. Polynomial Optimisation The problem of inferring the phylogenic tree of $n$ extant species from their genome is treated via mainly two approaches, the maximum parsimony and the maximum likelihood approach. While the latter is thought to produce more meaningful results, it is harder to solve computationally. We show that under a molecular clock assumption, the maximum likelihood model has a natural formulation that can be approached via branch-and-bound and polynomial optimization. Using this approach, we produce a counterexample to a conjecture relating to the reconstruction of an ancestral genome under the maximum parsimony and maximum likelihood approaches. This talk is part of the Isaac Newton Institute Seminar Series series. ## This talk is included in these lists:- All CMS events
- Featured lists
- INI info aggregator
- Isaac Newton Institute Seminar Series
- School of Physical Sciences
- Seminar Room 1, Newton Institute
- bld31
Note that ex-directory lists are not shown. |
## Other listsEngineers Without Borders CUiD - Cambridge University International Development Society BHRU Annual Lecture 2017## Other talksSir Richard Stone Annual Lecture: The Emergence of Weak, Despotic and Inclusive States Value generalization during human avoidance learning Glanville Lecture 2017/18: The Book of Exodus and the Invention of Religion Modelling mitochondrial dysfunction in Parkinsonâ€™s disease: mitophagy, calcium and beyond Dame Ottoline Leyser: Plant Development Prof Kate Jones (UCL): Biodiversity & Conservation |