Methods are urgently required to validate and improve these draft assemblies. We have developed several approaches to assess the quality of draft genome assemblies, identify regions of misassembly and correct assemblies. These approaches can be applied to a broad range of genomes which have either been completed or are undergoing development. In addition, we have developed methods for high resolution SNP discovery for the assessment of genome evolution and trait association in complex crop genomes. I will give examples of these applications to plant genomes of different size and complexity.
Characterising Plant Genomes The Good The Bad and The Ugly
Video Mar 30, 2015
Modern machine learning is great for helping scientists sort through huge data sets. But it’s less useful for things that require inference or reasoning – both vital to the scientific process. One group of scientists are now trying to fix this problem with a new kind of machine learning. This new approach aims to find the underlying algorithmic models that interact and generate data, to help scientists uncover the dynamics of cause and effect.WATCH NOW