Learning from watching genomes
Learning from watching genomes evolve
24 février 2020
Présentée par Mathieu Blanchette, Centre McGill de Bioinformatique, McGill University
The genomes of more than one hundred vertebrate genomes are now largely sequenced. How can one make use of this massive amount of evolutionary information to better understand the origin and function of portions of the human genome? In this talk, I will first discuss how the genomes of ancestral mammalian species can be reconstructed with surprisingly high accuracy from the genomes of extant species. I will then present how inferred ancestral sequences can be used to improve the detection of ancient evolutionary events such as transposable element and pseudogene insertions that have shaped mammalian genomes. Finally, I will then introduce algorithmic and machine learning approaches that make use of inferred ancestral DNA sequences to improve the accuracy of transcription factor binding site and micro-RNA target site prediction.