Software and Current Research Projects/Themes
- SubseT Optimization by Reference Matching (STORM) v2.0 (September 2017) and Resolution EnhanceD STORM (RED-STORM) are freely available from BitBucket (click images for links to BitBucket).
- MetaboNetworks v2.1 (September 2017) is freely available from the MATLAB File Exchange (v2.2 (June 2018) is available from BitBucket, click image for link to BitBucket).
- Covariate Adjusted PLS (CAPLS) v1.5 (June 2018) is freely available from BitBucket (click image for link to BitBucket).
- MetaboPathways v1.0 (June 2018) is freely available from BitBucket (click image for link to BitBucket).
Codes, example data and group data available using this link from the Box folder for the STRATiGRAD data treatment course (11/12/2018).
Codes and example data available using this link from the Box folder for the STRATiGRAD NMR Metabolite Identification course (29/04/2019).
Projects and Themes
- Rutherford Fund Fellowship at Health Data Research (HDR) UK "Identification of Metabolic Phenotypes and Systemic Biochemical Reaction Networks Associated with Human Blood Pressure" (MR/S004033/1)
- Robust multi-omic data fusion
- Multi-class clustering and prediction
- Network fusion and knowledge evolution
- MRes project (in collaboration with Dr Katia De Filippo) on Data visualization and analysis of intravital microscopy multi-layered video data using statistical machine learning undertaken by MRes in Cancer Informatics student Hoai-An Truong.
Host genomic influence on the gut microbial metabolite-blood pressure relationship, International Society of Hypertension conference, Kyoto, Japan, 2022
URINARY METABOLIC PHENOTYPE OF BLOOD PRESSURE, ESH ISH ON AIR Joint Meeting, Glasgow (online), 2021
An issue of life and breadth: how a urine test can help a nation on aslender bender, Health Data Research UK, London, 2020
Monitoring diet more accurately to aid healthy living (in a post-COVID society), Health Data Research UK, London, 2020
Integrating omics to understand blood pressure variation, MRC London Institute of Medical Sciences, London, United Kingdom, 2020
A Systems Biological Approach to the Interpretation of Multi-omics Data, Stellenbosch University, Stellenbosch, South Africa, 2019
Systemic nutriome-metabolome interactions to understand pathways to disease risk in humans, Murdoch University, Perth, Australia, 2019
Research Student Supervision
Alloula,A, Phenotypic Classification using Deep Learning in Metabolomics
Anholt,L, Leveraging geometric learning for community detection in biological networks that integrate polymorphic and metabolic data
Anholt,L, Expanding the systems view of biology and disease by integrating genome-wide association catalog data in the visualization of metabolic reaction networks
Chaitrakulthong,N, Expanding the systems view of colorectal cancer risk by integrating genome-wide association catalog data in the visualization of metabolic reaction networks with MetaboNetworks
Cheng,Z, A framework for spatial metabolomics data analysis of fatty liver disease and liver fibrosis
Faghih Mirzaei,N, What-the-bug?! Named entity recognition of bacteria and microbiota in biomedical text using recurrent neural networks
Gao,M, Data visualization and analysis of intravital microscopy multi-layered video (4D) data to identify how splenic neutrophils are controlled in their activation, location and migration by other splenic players
Hu,Y, Natural language processing of biomedical literature: automated mining of metabolome-wide association studies
Hydyrova,L, UROP: Creation of a Multi-Task Corpus for Metabolite, Enzyme and Pathway Named Entity Recognition
Ibrahim,M, Natural language processing of biomedical literature: automated mining of genome-wide association studies
Jarosinska,O, Multi population assessment of urinary metabolome stability over time
Jin,W, Auto-CORPus: Automated Abbreviation and Definition Detection of Biomedical Literature
Kasapi,M, Integration of faecal metabolic phenotypes and gut microbiota in subtypes of irritable bowel syndrome
Li,ZJ, “A picture is worth a thousand words”: translating images found in biomedical literature to text
Makraduli,F, Find The Assay: named entity recognition of techniques used for genome-wide and metabolome-wide association study data generation
McQuibban,NAR, GWAS Metadata Extraction: GWAS MNER
Money-Kyrle,S, Scaling As A Hyperparameter
Popovici,CM, Automated Mining of Preprint and Peer-reviewed Literature for Cohort Characteristics
Scotcher,J, Understanding the Role of Host-Microbiome Interactions in the Pathophysiology of Irritable Bowel Syndrome and Its Subtypes
Son,W, NLP in Radiology Report: Auto-Label Generation for CXR Image Classification
Stotzem,N, AstraZeneca Sponsored Project: Remodelling of immunometabolism in chronic liver disease using novel data integration and visualisation tools
Sun,A, Natural language processing of biomedical literature to support automated mining of genome-wide association studies
Talay,A, Natural language processing of biomedical literature to extract genome-wide association study data
Truong,A, Data visualization and analysis of intravital microscopy multi-layered video data using statistical machine learning
Tsagkarakis,N, Natural Language Processing to Standardize Biomedical Scientific Literature
Wang,M, Named Entity Recognition for enzymes in biomedical text
Xu,K, UROP: incorporating latent variables in ensemble methods
Yeung,C, MetaboListem and TABoLiSTM: Two Deep Learning Algorithms for Metabolite Named Entity Recognition