Tag Archives: evolutionary biology

Inference and informatics in a ‘sequenced’ world

Short lecture relating my recent work on real-time phylogenomics, implications for bioinformatics research and future directions of genomic/phylogenetic modelling to explicitly account for phylogeny, synteny and identity through coloured graphs.

University of Reading, 2nd August 2017

Slides [SlideShare]: cc-by-nd

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Using field-based DNA sequencing to accelerate phylogenomics

Invited seminar at the Department of Zoology, Oxford University, 30th November 2016.

Summary of our field-based real-time phylogenomics (MinION DNA sequencing) experiments this year, and applicability to broad-scale tree-of-life phylogenomics and macroevolutionary biology.

Slides [SlideShare]: cc-by-nd

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Real-time Phylogenomics

General science talk about the potential of real-time phylogenomics, delivered at the Jodrell Lecture Theatre, Kew Gardens, November 2nd 2015

Slides [SlideShare]: cc-by-nc-nd

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Interpreting ‘tree space’ in the context of very large empirical datasets

Seminar presented at the Maths Department, University of Portsmouth, 19th November 2014

Evolutionary biologists represent actual or hypothesised evolutionary relations between living organisms using phylogenies, directed bifurcating graphs (trees) that describe evolutionary processes in terms of speciation or splitting events (nodes) and elapsed evolutionary time or distance (edges). Molecular evolution itself is largely dominated by mutations in DNA sequences, a stochastic process. Traditionally, probabilistic models of molecular evolution and phylogenies are fitted to DNA sequence data by maximum likelihood on the assumption that a single simple phylogeny will serve to approximate the evolution of a majority of DNA positions in the dataset. However modern studies now routinely sample several orders of magnitude more DNA positions, and this assumption no longer holds. Unfortunately, our conception of ‘tree space’ – a notional multidimensional surface containing all possible phylogenies – is extremely imprecise, and similarly techniques to model phylogeny model fitting in very large datasets are limited. I will show the background to this field and present some of the challenges arising from the present limited analytical framework.

Slides [SlideShare]: cc-by-nc-nd

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Phylogenomic convergence detection: lessons and perspectives

Talk presented at the 18th Evolutionary Biology Meeting At Marseille (programme), 16th-19th September 2014.

(Powerpoint – note this is a draft, not the final talk, pending authorisation): EBMdraft

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