Grant success in 2016 and 2017

Discovery Grant Success:

Wilkins MR, Hart-Smith G
DP170100108 – The discovery of decision-making modules in protein interaction networks
Proposal Summary
This project aims to discover how cells use proteins to make decisions. This is important for all living things, which must react to stimuli to grow, adapt, defend themselves and to die. The project’s anticipated outcome is the systems-level identification of decision-making modules in an intracellular network. Its focus is on the smallest possible modules, which contain a decision-making protein with two modifications that control protein-proteins interactions. It will investigate two recurrent decision-making modules. The expected benefits of the project include new means to decipher biological complexity, and targets to modulate biosystems by genome editing or with drugs.

Linkage Grant Success:

Edwards R, Wilkins M, Tanaka M, Attfield P, Bell P
LP160100610 – Elucidating the genetic basis of newly evolved metabolic functions in yeast
Proposal Summary
This project intends to research how complex metabolic pathways originate and evolve. This project will use cutting edge genome sequencing and molecular techniques to elucidate the heritable genetic basis of Baker’s yeast, which has been the selectively evolved to use xylose as a sole carbon source: something vital for second generation biofuel production that wild yeast cannot do. This project will combine detailed molecular characterisation of highly adapted yeast strains with a novel “molecular palaeontology” approach to trace the evolutionary process and identify functionally significant loci under selection. Detailed characterisation of this trait will accelerate the development of future yeast strains and test fundamental evolutionary theories.
LIEF Grant Success:

Lews G, Wilkins M and 13 others
LE160100002 – Distributed Memory Cluster for the Intersect consortium of universities
Proposal SummaryThe NSW research community has a deep history of using High Performance Computing (HPC) to achieve major breakthroughs across a diverse range of disciplines including astrophysics, bioinformatics, environmental science, information technology and engineering. As the use of HPC increases, the application-specific needs of the research community become more diverse, requiring greater flexibility as well as higher performance. The present facility is no longer internationally competitive, and is hampering progress in cutting edge research. The (quantifiable descriptor) cluster will provide a greater than 10 fold increase and will advance ARC funded projects in diverse fields.