-
-resolution metagenomics and work with population genetics theory. This will cumulate in a new understanding of host-microbial interactions through acclimatization and adaptation, that will be validated in
-
Primary Supervisor - Prof David S Richardson Scientific Background Genetic variation within populations is essential to their ability to adapt and survive, but most mutations that change function
-
data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
-
approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
-
relatives and made our ancestors take over the world? This fundamental question remains unsolved. We can now tackle this from a new angle, leveraging the unprecedented genetic data available in biobank-scale
-
Primary supervisor - Dr Karl Grieshop Why do harmful genes persist in populations instead of being removed by natural selection? One answer lies in sexual antagonism: when a genetic variant benefits
-
replication and transcription. Using C. elegans genetics, advanced RNA biology techniques, and industrial biochemistry training with Inspiralis Ltd., the student will investigate how RNAs and their
-
, threatening global food security. We will identify the genetic and epigenetic changes associated with prolonged sub-culture of the blast fungus using comparative genome analysis and thereby define
-
subtype stx2a is linked to a higher chance of this progression and sequence-based surveillance has indicated increasing acquisition of this subtype across genetically diverse E. coli. In this project, we
-
plants. To better understand how distantly-related land plants defend themselves against pathogen infection, our group investigates the molecular genetic mechanisms controlling disease resistance in