My research interest is in studying cellular and molecular pathways of COVID-19 disease.
SEEK ID: https://fairdomhub.org/people/885
Expertise: Systems Biology, Mathematical modelling, Biotechnology, Synthetic Biology, Metabolic Engineering, metabolism, Metabolic Networks, SARS-CoV 2, COVID-19, Pathway Curation, Pathway Analysis, Network Analysis
- Programmes (2)
- Projects (2)
- Institutions (2)
- Investigations (1+3)
- Studies (1+2)
- Assays (0+4)
- Models (0+1)
- SOPs (0+1)
The Disease Maps Project is designed as a large-scale community effort. It is a network of groups that work together in order to better understand disease mechanisms. The project exchanges best practices, share information, develop tools to make it easier for all the involved groups to achieve their goals.
Projects: COVID-19 Disease Map
Web page: https://disease-maps.org
Projects that do not fall under current programmes.
Projects: Manchester Institute for Biotechnology, ICYSB 2015 - International Practical Course in Systems Biology, iRhythmics, INBioPharm, EmPowerPutida, Systo models, MycoSynVac - Engineering Mycoplasma pneumoniae as a broad-spectrum animal vaccine, Multiscale modelling of state transitions in the host-microbiome-brain network, Extremophiles metabolsim, NAD COMPARTMENTATION, Agro-ecological modelling, Bergen(Ziegler lab) project AF-NADase, NAMPT affinity, Stress granules, Modelling COVID-19 epidemics
Web page: Not specified
Here we share resources and best practices to develop a disease map for COVID-19. The project is progressing as a broad community-driven effort. We aim to establish a knowledge repository on virus-host interaction mechanisms specific to the SARS-CoV-2. The COVID-19 Disease Map is an assembly of molecular interaction diagrams established based on literature evidence.
Exploiting native endowments by re-factoring, re-programming and implementing novel control loops in Pseudomonas putida for bespoke biocatalysis. The EmPowerPutida project aims to engineer the lifestyle of Pseudomonas putida to generate a tailored, re-factored chassis for the production of so far non-accessible biological compounds. Pseudomonas putida is a bacterium with a highly versatile metabolism, including the capability to degrade or produce organic chemicals.
In this investigation we aim to develop automatic workflows to analyze COVID19 Omics data to understand and predict the molecular pathways depicting host-virus interaction.
Snapshots: No snapshots
In this study, we developed an automated and reproducible workflow for transcriptomics data analysis using network biology approaches. The analyses are fully automated in R with clusterProfiler and RCy3 to connect to the widely adopted network analysis software Cytoscape including the CyTargetLinker app for network extension. For demonstration, we use a publicly available dataset from Blanco-Melo et al., GSE147507 obtained from GEO. After pre-processing with DESeq2, the dataset contains log2 fold
Person responsible: Nhung Pham
Snapshots: No snapshots
Investigation: Omics data analysis workflow
Assays: No Assays