SLMS Academic Careers Office
- Clinical Academic Training
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- Grand Challenges
- 1. Bayesian Modelling of Disease Progression In juvenile dermatomyositis (JDM)
- 2. Mind-body interactions influencing the outcome of treatment for epilepsy
- 3. Treating retinal inflammation: bridging the divide between common problems in the eye and the brain
- 4. Development of a Novel In Vivo Animal Model for Schizophrenia Drug Testing
- 5. Immune mechanisms in Developmental Programming of Non-Alchoholic Fatty Liver Disease
- 10. Molecular Control of Pain Processing
- 11. Understanding the mechanisms of insulin secretion in patients with HADH mutations
- 12. Origins of cortico-subthalamic “hyperdirect” pathway in the motor cortex: electrophysiology and imaging
- 13. The mechanical control of tissue regeneration.
- 14. Investigating community severance in Southend and its effects on health and access to healthcare
- 15. Ageing of the liver and protection from injury: from flies to mice to humans
- 16. Intelligent nanomaterials against antibiotic resistant bacteria
- 17. Retroviral restriction factors that control species-specific gene regulation and stem cell fate
- 18. Improving women’s choice and uptake of effective contraceptive methods through development of interactive digital interventions
- 19. From embryonic cell to neuron: understanding the complexity of developmental decisions
- 20. Identification of mitochondrial biomarkers and therapeutic targets in pancreatic cancer
- 23. Television subtitling for deaf and hearing-impaired viewers: a route to improve English language skills for UK migrants with normal hearing
- 24. Large-scale phylogenomic mapping of domain architecture changes to elucidate gene function evolution
- 26. Real-time and nanometre-scale visualisation of membrane perforation in pathogen attack and immune response
- 29. Human amniotic fluid-derived induced pluripotent stem cells for the treatment of osteogenesis imperfecta.
- 31. Understanding the immunopathogenesis of juvenile-onset SLE: could targeting lipid biosynthesis control disease progression and reduce cardiovascular risk?
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19. From embryonic cell to neuron: understanding the complexity of developmental decisions
Supervisor Pair: Professor Claudio Stern and Dr Karen M Page
Potential Student’s Home Department: Biosciences / Cell & Developmental Biology
“Neural induction”, the process by which early embryonic cells acquire a neural fate, was classically viewed as a single response to a molecular signal produced by the “organizer”, the embryonic inducing tissue. However it now appears that it is a complex cascade of interlocking decisions, cells passing through successive states. The challenge now is to dissect the hierarchy and dynamics of the transitions between these states to build a Gene Regulatory Network (GRN), a model that will not only enable us to understand this particularly important process in neural development but also offering a unique opportunity to uncover the full complexity of the “computer program” driving a developmental decision.
We are using Next Generation Sequencing and Bioinformatics to identify the transcription factors (TFs) involved and how they are regulated by signals from the organizer, to define active enhancers associated with the TFs and to analyse them for binding sites for other TFs in the set. The student will perform experiments and modelling work. Experimentally, he/she will undertake in-vivo validation of the spatiotemporal regulation of the genes and use NanoString analysis to establish detailed dynamic relationships. This will be the starting point for building a predictive model of the GRN, including its dynamics. The predictions from this model will then be tested experimentally both in the embryo and in cultured embryonic cells and stem cells to validate and test the model in an iterative way.
This will generate a predictive model for the transition between early embryonic stem cell and the neural tube (the early nervous system). The secondary supervisor is studying how neural tube cells acquire specific identities in response to later signals. The student will help link these, leading to a comprehensive view of how the nervous system is built.
Value-added perspective: This project is not only cross-disciplinary but also highly collaborative. It is linked to a BBSRC grant in collaboration with Prof Andrea Streit (King’s College London). Dr Page is experienced in mathematical and computational approaches to modelling biological systems and is also collaborating with Dr James Briscoe (NIMR, Mill Hill) to model neurogenesis in the embryonic spinal cord. Complementarity in this project is therefore particularly strong. Not only does it involve an experimental lab with expertise in embryology and molecular biology and a group with mathematical and computational interests at UCL, but it also brings together 4 teams across 3 institutions (UCL, KCL and NIMR) that are also partners of the new Crick Institute. We envisage that the student will act as the connecting bridge between these groups and be involved in driving regular cross-group meetings to discuss the wider implications of the project.