Spatial statistics and Hidden Markov Modelling to improve the efficiency of a novel diagnostic test for cancer using Single molecule imaging.
This project is in the rapidly developing field of single molecule imaging, that seeks to gain biological insights on the scale of 0-200nm (below the diffraction limit of conventional light microscopy). Working closely with collaborators at STFC, world leaders in the development and exploitation of single molecule imaging techniques, this project seeks to facilitate the automatic exploitation of spatial-data derived from a single molecule imaging technique pioneered by the OCTOPUS group called Fluorescence Localisation Imaging with Photobleaching (FLImP) the subject of two Nature Comms papers [1,2]. This technique is used to measure the arrangement of protein clusters (oligomers) on the cell membrane. The different conformation these proteins adopt is known to play a role in the development of cancer. The ability to measure the population of shapes of these protein clusters adopt can be used as a novel diagnostic test for cancers such as small cell lung carcinomas.
As every patient’s cancer is unique, this work is being undertaken with a view to developing novel diagnostic tools in order to rapidly fingerprint protein oligomerisation states in order to determine the most effective therapeutic strategy for each patient. Developing clinically translatable tools for such a personalised medicine approach requires full automation of the imaging technique in conjunction with fully tractable statistical techniques for the rapid analysis and exploitation of data generated, which these projects seek to support.
The FLImP single molecule imaging technique was pioneered by Professor Martin-Fernandez, Dr Rolfe and Dr Needham is capable of resolving molecular separations on the scale of 5 nanometers. FLImP has been used to investigate the oligomeric organisation of Epidermal Growth Factor Receptor (EGFR), which plays a central role in many human cancers. The OCTOPUS group at the STFC have been working to extend the FLImP technique to two dimensions and translate this technology to the clinic for use as a tool for cancer diagnosis with collaborators at Kings College London. As part of this work Dr Davis & Dr Rolfe have been automating the FLImP acquisition and analysis technique to increase throughput. To date, the £1.3 Million FLImP microscope facility at STFC is generating 1 Terabyte of imaging data every 24 hours from which molecular separations are automatically determined and analysed. A key stage in the analysis process is rapidly determining which of the 1 million or so fluorophores extracted each day is suitable for FLImP analysis. This is achieved by labelling and segmenting 1-dimensional plots of integrated fluorophore intensity profiles over time containing two or more fluorophore photobleaching events. As the behaviour of each fluorophore can be described using a markov chain, an efficient Hidden Markov modelling approach could
be used to maximise information extraction from these datasets.
A second arm of this project is concerned with improving the automation and exploitation of spatial statistical data generated by a second, complimentary, single molecule imaging microscopy technique called MINFLUX. MINFLUX is a recently developed single molecule imaging technique capable of resolving fluorophores in 3-dimensions to a resolution of 1-3nm . While not as mature as FLImP, this exciting technology has the potential to transform our understanding of biological systems at this spatial scale. Currently, analysis of MINFLUX data is extremely heuristic and labour intensive. For wide adoption of this technology, the development of automation and novel analysis tools are required. MINFLUX data is acquired in the form of Neyman-Scott point pattern processes, where daughter locations represent fluorophore localisations (of which there are many) and the unseen parent points represent the most likely position of the emitting fluorophores.
An opportunity has arisen for a statistically gifted PhD student to develop a novel Hidden Markov model to facilitate automatic labelling and segmentation of FLImP suitable fluorophore bleaching events from these integrated intensity profiles from simulated and real world data. The objective of this project will be to develop the algorithms behind the hidden Markov model. The model will need to be robust to account for noise, partial information (two or more fluorophore bleaching events may happen at the same time) and any potential
outliers within the data and will need to be computationally efficient to ensure it is practical to apply at volume. The model will also need to take into account the replicated experimental processes with the incorporation of random effects. Hidden Markov models such as the factorial hidden Markov model and the hidden semi Markov model will be investigated and the algorithms behind the models (Viterbi, Forward- backward) developed. The ultimate goals of this project are to maximise information extraction from the existing FLImP data archive (¿450 Terabytes of FLImP imaging data) and accelerate future FLImP data acquisition. This
fits into my current research in terms of hidden Markov model development.
As part of this project we seek to develop novel techniques to rapidly assess the information content of sampled Neyman-Scott processes (essentially MINFLUX datasets as they are being acquired) to rapidly evaluate the likely quality of a region of interest. This is an important research question given the considerable time required to image a region of interest using MINFLUX, and the difficulty of making this distinction by eye. The main objective of this project will be to develop machine learning algorithms in conjunction with spatial point pattern analysis and taking into account fractal analysis. We are also seeking to reconstruct the most likely parent process that gave rise to a series of MINFLUX daughter localisations and from this parent process, reconstruct the most probable molecular structure(s) that gave rise to this process. This will involve the development of spatial statistics to understand the parent process within the Neyman-Scott point pattern and develop techniques to be able to uncover these as well as the molecular structure that gave rise to the process.
 Nature Comms 9, Article number: 4325 (2018)
 Nature Comms 7, Article number: 13307 (2016)
 Nat Methods 17, 217–224 (2020)
 JORS 7, 1-13 (2020)
 SMTDA, 79, (2018)
 CASI, (2018)
The Mathematical Research Centre conducts world-class research in the following areas: Algebra, Analysis, Operator Algebras, Algebraic Topology, Topological Data Analysis, PDEs, Survival Analysis, Bayesian Networks, Data Analytics and Operational Research. It maintains vibrant international links with a large number of researchers around the globe and regularly hosts international conferences and research visitors.
Mathematics at Queen's is joint 1st for Research Intensity in the UK. Queen’s is ranked in the top 170 in the world for graduate prospects (QS Graduate Employability Rankings 2022)
List of researchers, their interests and upcoming PhD projects can be found at:
Mode of study / duration
Registration is on a full-time or part-time basis, under the direction of a supervisory team appointed by the University. You will be expected to submit your thesis at the end of three years of full-time registration for PhD, or two years for MPhil (or part-time equivalent).
- The School has many industry links, some of which are with Seagate Technology R&D, Andor Technology and AVX Ltd. Many of our graduates take up positions with these companies in posts such as Statistical Analysis Programmer, Trainee Accountant, Financial Engineer and Business Analyst.
- Queen’s is ranked in the top 170 in the world for graduate prospects (QS Graduate Employability Rankings 2022). Graduates from the School take up employment through a number of companies such as Allstate, AquaQ Analytics, Citigroup, Deloitte, PwC, Randox, Seagate and UCAS.
World Class Facilities
- Since 2014, the School has invested over £12 million in new world-class student and staff facilities. Maths and Physics students now have their own teaching centre that opened in 2016 housing experimental physics laboratories, two large computer rooms for mathematical simulations and student study plus a student interaction area.
In addition, Belfast is one of the lowest student cost of living in the UK (Which? University, 2018).
- Students will have access to our facilities, resources and our dedicated staff. The School of Mathematics and Physics is one of the largest Schools in the University. Staff are involved in cutting-edge research that spans a multitude of fields.
After an undergraduate degree in QUB, I started my PhD journey in pure mathematics research. In the four years of study, there are two invaluable features. Firstly I received ideal supervision which helped me to solve my research problems and to touch the contemporary research work. Secondly the system is very free whereby I can study, consider and discuss the relevant maths knowledge and problems which are not directly related to my research but very helpful for my future research work.
Weijiao Hu, PhD Mathematics, 2019
Overall, 90% of research submitted to the REF 2021 by the School of Mathematics and Physics was judged as internationally excellent or world-leading.
Information on the research interests and activities of academics in the Mathematical Science Research Centre can be found at https://web.am.qub.ac.uk/wp/msrc/. These interests fit into the themes: Algebra, Analysis, Data Science, Optimization and Operational Research, Partial Differential Equations, Statistics, Topology and Geometry.
Research Impact in Mathematics at Queen’s is gained through having wide interactions with Industry and the Public Sector which enhances and accelerates societal and economic impact. In the REF 2021 results, 75% of impact in Mathematics was graded as 4* which demonstrates that the quality of impact is world-leading in terms of originality, significance and rigour.
Mathematical and statistical skills are in great demand in the economy, particularly the advanced skills developed at the PhD level.
Employment after the Course
As well as continuing in research careers, our PhD graduates have also gone on to work in finance, computing, data analysis, management and teaching. Our advisors will be happy to provide further information on the career prospects arising from your chosen research area. Further information on careers can be obtained from the School and the Faculty.
People teaching you
Dr David Barnes
Head of Centre - Mathematical Sciences Research Centre
Dr Ying-Fen Lin
Postgraduate Advisor - Mathematical Sciences Research Centre
Course structureThere is no specific course content as such. A PhD programme runs for 3-4 years full-time or 6-8 years part-time. Students can register for a writing up year should it be required.
The PhD is open to both full and part time candidates and is often a useful preparation for a career within academia or consultancy.
Please review the eligibility criteria on the webpages. If you believe that you meet these criteria then follow the steps below:
Select ONE potential supervisor from our list of Academic Staff: https://www.qub.ac.uk/courses/postgraduate-research/find-a-phd-supervisor/ and send an email to that supervisor advising that you are interested in studying for a PhD, stating when you would start, and how you would plan to fund the research. It would be helpful to provide a a brief statement of the research question or interest, and how you think the question could be investigated. The potential supervisor may invite you to meet with them or they may invite you to apply formally.
Assessment processes for the Research Degree differ from taught degrees. Students will be expected to present drafts of their work at regular intervals to their supervisor who will provide written and oral feedback; a formal assessment process takes place annually.
This Annual Progress Review requires students to present their work in writing and orally to a panel of academics from within the School. Successful completion of this process will allow students to register for the next academic year.
The final assessment of the doctoral degree is both oral and written. Students will submit their thesis to an internal and external examining team who will review the written thesis before inviting the student to orally defend their work at a Viva Voce.
Supervisors will offer feedback on draft work at regular intervals throughout the period of registration on the degree.
Students will enjoy the benefits of modern practical laboratories, extensive computer facilities and interactive spaces. Students will be provided with their individual workspace.
The minimum academic requirement for admission to a research degree programme is normally an Upper Second Class Honours degree from a UK or ROI HE provider, or an equivalent qualification acceptable to the University. Further information can be obtained by contacting the School.
For information on international qualification equivalents, please check the specific information for your country.
English Language Requirements
Evidence of an IELTS* score of 6.0, with not less than 5.5 in any component, or an equivalent qualification acceptable to the University is required. *Taken within the last 2 years.
International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.
For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.
If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.
|Northern Ireland (NI) 1||£4,596|
|Republic of Ireland (ROI) 2||£4,596|
|England, Scotland or Wales (GB) 1||£4,596|
|EU Other 3||£18,900|
1 EU citizens in the EU Settlement Scheme, with settled or pre-settled status, are expected to be charged the NI or GB tuition fee based on where they are ordinarily resident, however this is provisional and subject to the publication of the Northern Ireland Assembly Student Fees Regulations. Students who are ROI nationals resident in GB are expected to be charged the GB fee, however this is provisional and subject to the publication of the Northern Ireland Assembly student fees Regulations.
2 It is expected that EU students who are ROI nationals resident in ROI will be eligible for NI tuition fees. The tuition fee set out above is provisional and subject to the publication of the Northern Ireland Assembly student fees Regulations.
3 EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.
All tuition fees quoted are for the academic year 2021-22, and relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.
There are no specific additional course costs associated with this programme.
Additional course costs
Depending on the programme of study, there may also be other extra costs which are not covered by tuition fees, which students will need to consider when planning their studies . Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £100 per year for photocopying, memory sticks and printing charges. Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen. There are also additional charges for graduation ceremonies, and library fines. In undertaking a research project students may incur costs associated with transport and/or materials, and there will also be additional costs for printing and binding the thesis. There may also be individually tailored research project expenses and students should consult directly with the School for further information.
Some research programmes incur an additional annual charge on top of the tuition fees, often referred to as a bench fee. Bench fees are charged when a programme (or a specific project) incurs extra costs such as those involved with specialist laboratory or field work. If you are required to pay bench fees they will be detailed on your offer letter. If you have any questions about Bench Fees these should be raised with your School at the application stage. Please note that, if you are being funded you will need to ensure your sponsor is aware of and has agreed to fund these additional costs before accepting your place.
How do I fund my study?1.PhD Opportunities
Find PhD opportunities and funded studentships by subject area.2.Funded Doctoral Training Programmes
We offer numerous opportunities for funded doctoral study in a world-class research environment. Our centres and partnerships, aim to seek out and nurture outstanding postgraduate research students, and provide targeted training and skills development.3.PhD loans
The Government offers doctoral loans of up to £26,445 for PhDs and equivalent postgraduate research programmes for English- or Welsh-resident UK and EU students.4.International Scholarships
Information on Postgraduate Research scholarships for international students.
Funding and Scholarships
The Funding & Scholarship Finder helps prospective and current students find funding to help cover costs towards a whole range of study related expenses.
How to Apply
Find a supervisor
If you're interested in a particular project, we suggest you contact the relevant academic before you apply, to introduce yourself and ask questions.
To find a potential supervisor aligned with your area of interest, or if you are unsure of who to contact, look through the staff profiles linked here.
You might be asked to provide a short outline of your proposal to help us identify potential supervisors.