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We are a computational biology group in SIPBS (Strathclyde Institute for Pharmacy and Biomedical Sciences), working in microbial genomics, bioinformatics software development, biostatistics, and systems biology. https://sipbs-compbiol.github.io/

Getting the advert ready just now, but we'll soon be accepting applications for an IBioIC-funded Collaborative Training Partnership with @hutton.ac.uk The project is to infer "rules" for composing carbohydrate-active enzyme (CAZyme) arsenals in bacterial plant pathogens. UK funding only.

Lignocellulose is a globally abundant, renewable carbon source with promise for fossil fuel replacement in energy generation and as feedstock for synthetic processes. Industrial conversion of lignocellulosic biomass is currently inefficient. Pectobacteriaceae are plant pathogens that break down host plant material using carbohydrate-active enzyme (CAZyme) mixtures that act in concert. Pilot studies show these enzymes have potential to improve biofuel production efficiency. Lignocelluosic biomass composition is highly varied. Design of effective CAZyme mixtures for lignocellulose degradation is difficult. Only a minority of CAZymes have so far been characterised. Practical screens of CAZymes (an organism’s CAZome) can be slow and resource-intensive. Bioinformatic analysis of microbial genomes may help accelerate design of industrially useful CAZyme mixtures.We mined CAZomes across the Pectobacteriaceae to identify co-evolved CAZyme mixtures, gaining potential insight into the host adaptation of these pathogens, using the cazomevolve1 software package.