Royal (Dick) School of Veterinary Studies / The Roslin Institute
The objective of this industrial case studentship is to provide multidisciplinary training in machine learned data-integration leading to the identification and bio-validation of factors capable of regulating homeostatic maintenance of the nervous system.
There are publicly accessible and privately held research information resources whose artificial intelligence mediated mining promises to plug knowledge gaps surrounding the regulation of nervous system stability and in turn (outwith the scope of this studentship), development of novel stratified and precision regenerative medicines.
This industrial case studentship combining training from Massive Analytic and access to state of the art platforms, with an interdisciplinary supervisory academic team will develop machine learned data-integration leading to the identification (and subsequent bio-validation) of regulators of nervous system development, homeostatic maintenance and postnatal ageing. Such factors would be future foci of broadly applicable therapeutic interventions to improve age related health span and response to degeneration inducing stimuli.
This will be achieved through a unique academic/industrial collaboration to integrate commercially leading artificial intelligence platforms for multimodal data analysis provided by an industrial partner, Massive Analytic (https://www.massiveanalytic.com
) with multidisciplinary academic human and animal model expertise in neuronal loss and dysfunction, pluripotent stem cell technology, and medical centric informatics and machine learning.
Loss and dysfunction of brain region selective neuronal synapses is a characteristic feature of “normal healthy” ageing as well as all congenital and adult onset neurological disorders. Elucidating how synaptic alterations associated with advancing-age and/or genetic perturbations leave a neuron vulnerable is essential for our understanding of what regulates nervous system stability in health and disease, but also to the development and design of neuroprotective strategies.
Dr Wishart has led comparative proteomic analyses in animal models and humans, which have identified ageing related, brain region selective regulators of both synaptic and axonal stability in vivo in neurodegenerative and neurological disorders and healthy ageing (Cell Rep 2019, 27(4): 1018-1026).
Dr De Sousa has led the development and use of human pluripotent stem cells for discovery and therapy, and roles of ambient and epigenetic mechanisms affecting cell regeneration (Stem Cell Res 2019, 34:101358).
Dr Luz has computationally modelled behavioural and biological changes caused by neurodegenerative diseases, enabling future improvements in stratification and precision of treatments (BMJ 2019 22(3): 504-517).
Here, the candidate will be trained with Massive Analytic’s Oscar Multi-parameter Integrative Data Science platform made available to the project subscription-free. This will be applied to Wishart lab neuronal proteomes from cross-species normal healthy ageing, as well as those from congenital and adult onset neurological disorders, model systems, and publicly available human and animal model omics data to refine current hypotheses of what governs and regulates the stability of the nervous system in health and disease.
This will result in candidates with the potential to act as associated biomarkers for and/or regulators of stability and/or susceptibility as well as having implications for future therapeutic intervention.
Thus, such candidates will then be validated in human pluripotent stem cell and invertebrate (Drosophila) models for ability to modulate stability and/or morphology of the nervous system.
All candidates should have or expect to have a minimum of an appropriate upper 2nd class degree. To qualify for full funding students must be UK or EU citizens who have been resident in the UK for 3 years prior to commencement.