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Interactome visualisation of ALS using virtual reality


Project Description

Visualising high dimensional data is challenging and a significant constraint is the need to render in 2D for the screen or page. With the arrival of virtual reality (VR) and augmented reality (AR) comes the opportunity to explore and share biomedical data in new ways. VR/AR can extend 2D analyses intuitively to higher dimensions, providing richer interaction with data. Critically, they also provide us with new ways to explore the topological structure of data, particularly valuable for network graphs of arcs and vertices. 2D renders of network graphs are inherently ambiguous due to the crossing of arcs, something that grows polynomially with graph size, making large graphs unintelligible. 3D rendering eliminates this problem completely.

Network graphs are routinely used to depict the Interactome: the networks of interactions that drive physiological function. We will develop the first VR tools to facilitate 3D rendering, navigation and manipulation of the pathways of cell, gene, protein and small molecule interactions that drive the interactome. The tools will be enable the interactome to be embedded in other renderings, such as the spatial structure of cells, tissues, organs or organisms and can be reused across diseases. As an exemplar, the tools will be first applied to disrupted cellular processes in the motor neuron disorder, Amyotrophic Lateral Sclerosis (ALS). By cross-relating the structure of the human molecular interaction network against genomic data, we have previously identified clusters of interacting genes with newly identified mutations that we believe are involved in the development of ALS. 3-D modelling will greatly help us to understand their role in disease development.

Pathways of the interactome are routinely described using the Systems Biology Graphical Notation (SBGN), an open, community-driven 2D mapping standard [1] adopted by many software tools [2]. We propose to develop it for 3D visualisation. SBGN3D will exploit the Google Cardboard framework [3], facilitating visualisation using cheap viewers and phone apps, or as interactive models embedded in 2D digital content.

Aim 1: Translation of SBGN from 2D to 3D
* Develop 3D glyphs corresponding to 2D glyphs.
* Define compartment structure and text orientation.
* Extend current SBGN file formats to SBGN3D.
Aim 2: Development of SBGN3D viewer in Google Cardboard
* Develop import/export libraries for SBGN3D files.
* Build navigation interface for controlling SBGN3D maps.
* Export interface as phone app.
Aim 3: ALS application.
* Curate new ALS interactome maps to SBGN3D.
* Identify topological structure of ALS interactome.
* Export ALS SBGN3D maps to public repositories for reuse.

This project will yield:-
* The first schema for 3D mapping of the pathways of the interactome.
* The first toolset for viewing 3D pathway structures in VR environments.
* A richer understanding of ALS interactome topology VR schema/tools are the first step to AR modelling, the goal of follow up work.

Supervisors
* Dr Steven Watterson
• Prof Damien Coyle
• Dr William Duddy

Desirable Criteria
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
• Demonstrable programming skills and mathematical ability.
• Familiarity with biomedical science is desirable, but not essential.
• Completion of Masters at a level equivalent to commendation or distinction at Ulster is desirable, but not essential.
• A background in computer science, mathematics, physics, bioinformatics, biomedical science, stratified/personalised medicine, biomedical engineering, or another quantitative science.

Essential criteria
• To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.
• Sound understanding of subject area as evidenced by a comprehensive research proposal

Funding Notes

The University offers awards to support PhD study and applications are invited from UK, EU and overseas applicants. View Website for details of funding.

References

[1] Le Novere N, et al., Nat Biotech (2009) 27(9), 864-864.
[2] https://sbgn.github.io/.
[3] https://developers.google.com/cardboard.

How good is research at Ulster University in Allied Health Professions, Dentistry, Nursing and Pharmacy?
Biomedical Sciences

FTE Category A staff submitted: 74.10

Research output data provided by the Research Excellence Framework (REF)

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