Projects per year
Personal profile
Academic Biography
Dr Xinzhong Li obtained his Bsc., MSc, and PhD. degrees from Xi'an Jiaotong University, China. Before recently joined in TEES, he worked at Plymouth University for six years and Imperial College London for 10 years.
Summary of Research Interests
Dr Li's research interest lies in system biology and bioinformatics including machine learning and next-generation sequencing
Research Projects & External Funding
- 2022 - 2026, Europe Horison MSCA-DN TClock4AD: Targeting Circadian Clock Dysfunction in Alzheimer’s Disease (€3.9m). Coordinated by University of Bologna to train 15 PhD students with double degrees. Two PhD students with €615k will be allocated to Teesside University
- 2022-2024, The Royal Society International Exchanges 2021: Circular RNA regulates gene expression in brain cancer. With Dr Gaetano Gargiulo at Max-Delbrück-Center for Molecular Medicine (MDC) Berlin. £12,000
- 2018-2021, H2020 MSCA-ITN-ETN AiPBAND: An Integrated Platform for Developing Brain Cancer Diagnostic Techniques. 4-year project with a whole budget of 3.68m Euro. PI and Scientific Coordinator. Project website: https://www.aipband-itn.eu/
- 2017-2020, H2020 MSCA-ITN BBDiag: Blood Biomarker-based Diagnostic Tools for Early Stage Alzheimer’s Disease. 4-year project with a whole budget of 3.45m Euro. Co-investigator. Project website: http://www.bbdiag-itn-etn.eu/
- 2017-2018, Breath-based non-invasive diagnosis of Alzheimer’s disease: A pilot study. One-year project with a whole budget of £52,120. PI. Project website: https://www.plymouth.ac.uk/research/ims-alzheimers
External Research Collaborations
Prof. James Scott at Imperial College London
Prof. Genhua Pan at Plymouth University
Prof. Yike Guo at Imperial College London
Dr. Taigang He at St Georgy University London
PhD and Research Opportunities
A fully funded PhD studentship is availble now.
The development of cancer-on-chip preclinical model for glioblastoma
https://www.tees.ac.uk/sections/research/funding_details.cfm?fundingID=214
Fingerprint
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Network
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AiPBAND: An Integrated Platform for Developing Brain Cancer Diagnostic Techniques
1/01/18 → 30/06/22
Project: Research
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A Systematic Research Methodology for Business Model Decision Making in Commercialising Innovative Healthcare Diagnostic Technologies
Ong, A., Liu, S., Pan, G. & Li, X., 13 May 2022, Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs. ICDSST 2022: Proceedings. Cabral Seixas Costa, AP., Papathanasiou, J., Jayawickrama, U. & Kamissoko, D. (eds.). Springer, 13 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter
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Early Detection of Alzheimer's Disease with Blood Plasma Proteins using Support Vector Machines
Eke, C., Jammeh, E., Li, X., Carroll, C., Pearson, S. & Ifeachor, E., 27 Apr 2020, In: IEEE Journal of Biomedical and Health Informatics.Research output: Contribution to journal › Article › peer-review
Open AccessFile53 Downloads (Pure) -
Genetic networks in Parkinson's and Alzheimer's disease
Kelly, J., Moyeed, R., Carroll, C., Luo, S. & Li, X., 23 Mar 2020, In: Aging. 12, 6, p. 5221-5243 23 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile76 Downloads (Pure) -
Large-Scale Analysis Reveals Gene Signature for Survival Prediction in Primary Glioblastoma
Prasad, B., Tian, Y. & Li, X., 1 Sep 2020, In: Molecular Neurobiology. 57, 12, p. 5235–5246 12 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile48 Downloads (Pure) -
Breath-based non-invasive diagnosis of Alzheimer’s disease: A pilot study
Tiele, A., Wicaksono, A., Daulton, E., Ifeachor, E., Eyre, V., Clarke, S., Timings, L., Pearson, S., Covington, J. & Li, X., 9 Dec 2019, (E-pub ahead of print) In: Journal of Breath Research.Research output: Contribution to journal › Article › peer-review
Open AccessFile169 Downloads (Pure)
Datasets
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Additional file 2 of Fused inverse-normal method for integrated differential expression analysis of RNA-seq data
Prasad, B. (Creator) & Li, X. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.20444128.v1, https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Fused_inverse-normal_method_for_integrated_differential_expression_analysis_of_RNA-seq_data/20444128/1
Dataset
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Additional file 3 of Fused inverse-normal method for integrated differential expression analysis of RNA-seq data
Prasad, B. (Creator) & Li, X. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.20444131, https://springernature.figshare.com/articles/dataset/Additional_file_3_of_Fused_inverse-normal_method_for_integrated_differential_expression_analysis_of_RNA-seq_data/20444131
Dataset
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Additional file 4 of Fused inverse-normal method for integrated differential expression analysis of RNA-seq data
Prasad, B. (Creator) & Li, X. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.20444134.v1, https://springernature.figshare.com/articles/dataset/Additional_file_4_of_Fused_inverse-normal_method_for_integrated_differential_expression_analysis_of_RNA-seq_data/20444134/1
Dataset
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Additional file 1 of Fused inverse-normal method for integrated differential expression analysis of RNA-seq data
Prasad, B. (Creator) & Li, X. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.20444125.v1, https://springernature.figshare.com/articles/journal_contribution/Additional_file_1_of_Fused_inverse-normal_method_for_integrated_differential_expression_analysis_of_RNA-seq_data/20444125/1
Dataset
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Additional file 3 of Fused inverse-normal method for integrated differential expression analysis of RNA-seq data
Prasad, B. (Creator) & Li, X. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.20444131.v1, https://springernature.figshare.com/articles/dataset/Additional_file_3_of_Fused_inverse-normal_method_for_integrated_differential_expression_analysis_of_RNA-seq_data/20444131/1
Dataset