Summary

COVID-19 is the disease responsible for the biggest pandemic crisis since the Spanish flu. Several studies have been conducted and linked COVID-19 severity to the patient’s microbiomes from different body parts. However, the role of such microorganisms in the pathogenesis of Covid infection and the long-Covid syndrome is yet to be understood. Based on the ongoing collaboration, this proposal aims to develop a deep learning-based multiplexed metagenomics approach for the identification of key network biomarkers associated with Covid-19 severity based on human oral microbiomes.

Methodology:

The project aims to achieve the following three objectives via a deep multiplexed metagenomics approach:

1. Inference of microbial co-occurrence networks associated with COVID severity:This will be achieved based on our previous research, in which a framework was introduced to mitigate the composition effect in the inference of significant associations between microbiome. A deep learning-based multiplex network model then will be developed for integrative analysis of co-occurrence to bridge together different co-presence and mutual-exclusion relations and to facilitate the crosstalk and interactions between co-occurrence networks.

2. Dynamical network analysis for identifying key network biomarkers linking to COVID-19 progression: This will be fulfilled based on the concept of dynamic network biomarkers which has been proposed to detect early-warning signals during the disease progression at the molecular network level. Output from Objective 1 will be incorporated to develop a new framework, DeepMeta, to identify the critical stage of phenotypic changes, i.e. from normal to long Covid, during which dramatic changes in the abundance of microbiome components led to differentiation of the phenotypes.

3. Biomarker explanation and evaluation: Biomarker data will be used for meta comparisons to evaluate the proposed DeepMeta framework. The proposed methods and tools will be evaluated using the nasopharynx microbial community of 72 patients that developed different severity levels of COVID-19 released by our collaborators at the first instance.


Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.


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.

  • Masters at 75%
  • Sound understanding of subject area as evidenced by a comprehensive research proposal
  • Publications record appropriate to career stage

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,840 (tbc) maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Vice-Chancellor’s Research Bursary (VCRB)

Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees and provide the recipient with £8,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Vice-Chancellor’s Research Fees Bursary (VCRFB)

Fees only award (PhD fees + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £15,840 (tbc) per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

  • Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
  • Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
  • Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
  • Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living


Recommended reading

Wassan, J. T., Zheng, H., & Wang, H. (2021). Role of Deep Learning in Predicting Aging-Related Diseases: A Scoping Review. Cells, 10(11), 2924. Zheng, H., Wang, H., Dewhurst, R., and Roehe, R. (2018) Improving the Inference of Co-occurrence Networks in the Bovine Rumen Microbiome, IEEE/ACM Transactions on Computational Biology and Bioinformatics. DOI: 10.1109/TCBB.2018.2879342.

Wang, H., Pujos-Guillot, E., Comte, B., de Miranda, J. L., Spiwok, V., Chorbev, I., ... & Zheng, H. (2021). Deep learning in systems medicine. Briefings in Bioinformatics, 22(2), 1543-1559.

Wang, H., Zheng,H., Wang,J., Wang, C. and Wu, F. (2016) Integrating Omics Data with a Multiplex Network-based Approach for the Identification of Cancer Subtypes, IEEE Transactions on Nanobioscience, pp.335-342

Yang, B. et al. (2018) Dynamic network biomarker indicates pulmonary metastasis at the tipping point of hepatocellular carcinoma. Nat Commun 9, 678

Ventero, M. P., Cuadrat, R. R. C., Vidal, I., Andrade, B. G. N., Molina-Pardines, C., Haro-Moreno, J. M., et al. (2021). Nasopharyngeal Microbial Communities of Patients Infected With SARS-CoV-2 That Developed COVID-19. Frontiers in Microbiology 12, 1–10. doi:10.3389/fmicb.2021.637430.

Xu, W., Duan, L., Zheng, H., Li-Ling, J., Jiang, W., Zhang, Y., ... & Qin, R. (2021). An Integrative Disease Information Network Approach to Similar Disease Detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics.


The Doctoral College at Ulster University


Reviews

I started my PhD at Ulster University in Oct. 2017 after I received my master degree from Jiangsu University, China. My research interests are deep learning, natural language processing.I had a wonderful time during my stay at Ulster University, Jordanstown. Many thanks to all my supervisors, colleagues and research staff for their great help!

Chunlin Xu - PhD in Computing

I started my PhD at Ulster University after I received the master degree in computer application and technology from the School of Mathematics and Computer Science, Fujian Normal University, China.My research interests are feature extraction, face verification and pattern recognition.The proudest moments of my PhD when my papers were accepted by journals and I received my PhD certificate.It is a long journey to pursue a PhD, I couldn't have got through this without the constant support, help and encouragement from my supervisors and friends. Many thanks all of them.

Huan Wan - PhD in Computer Science and Informatics

I received the bachelor’s of engineering degree in computer science and technology from Shangrao Normal University, Jiangxi, China, in 2013; and the master’s degree in computer application and technology from the School of Mathematics and Computer Science, Fujian Normal University, China. When I was pursuing a PhD degree at Ulster University, I continued my research on face recognition and image representation.This long journey has only been possible due to the constant support and encouragement of my first supervisor. I also like to thank my second supervisor for his patience, support and guidance during my research studies. My favourite memory was the days of exercising, gathering and playing with my friends here. If I could speak to myself at the start of my PhD, the best piece of advice I would give myself would be "submit more papers to Journals instead of conferences".

Xin Wei - PhD in Computer Science and Informatics

After master’s degree, I joined the Artificial Intelligence Research Group in the School of Computing at Ulster University to pursue my PhD. I would like to thank my supervisors for their guidance, invaluable advice, encouragement and support throughout my PhD.My proudest moments were when my research papers were accepted in prestigious conferences and journals. I feel accomplished about the six first-author publications from my doctoral research. Also, I have had the honour of receiving the Best Student Paper Award at the 2018 International FLINS Conference.I love travelling; my favourite memories were travelling to present my research in addition to getting the opportunity to meet leading researchers from different parts of the world. And I couldn't have achieved this without the support of my friends and family.

Niloofer Shanavas - PhD in Computer Sciences and Informatics

I joined Ulster University in September 2017 right after obtaining my master's degree in Computer Science from Kyungpook National University, Daegu, South Korea. My research focus has been on deep neural network applications to natural language processing. Was happy that my PhD work on developing techniques to improve the performance of neural machine translation models to enhance communication between individuals speaking different languages. As a young person growing up in Ghana, I initially wanted to study for a degree in Medicine but had a change of heart when I discovered the potential benefits of studying Computer Science and Engineering during my undergraduate study at Kwame Nkrumah University of Science and Technology (KNUST), Ghana. This has been one of the best decisions I have ever taken.I have always wanted to pursue my education towards a PhD, and I am very glad that I have been able to achieve that. I had a wonderful time at Ulster University and was able to make some

Isaac Ampomah - PhD in Computing

In the whole PhD ordeal, my supervisory team played a tremendous role:- they are three in a million. They are perfect supervisors who perfectly know which milestones or pathways to be taken during research initiatives, and they understand the roles of virtually all stages in the journey of PhD. They showcased superior abilities in managing and motivating me evoking high standards; demonstrating a commitment to excellence. Jane and Haiying guided me as their daughter and Fiona turned out to be the best of friends.I heard from “Eleanor Roosevelt” that “The future belongs to those who believe in the beauty of their dreams.” The dream with which I grew up to become a Doctor one day, has finally come true. In the journey of PhD, I embraced that a PhD is not just the highest degree in Education but rather it is a life experience where perseverance is the key. I can never forget words from my external examiner Prof Yike Guo, from Imperial College London. His words

Jyotsna Talreja Wassan - PhD in Computer Science and Informatics