Pancreatic-Fibrosis logic-based model Version 1
We constructed a logic-based model to unravel mechanisms underlying pancreatic cancer and fibrosis. Model was calibrated with expression data and simulated for stimulus response and perturbation analysis to identify disease markers. Disease markers predicted by the model are validated through patient data using KM survival plot (which stratify patient into short and long survival) and box plot (expression level of the markers in normal vs. pancreatic patients). In vitro validations of the model are in progress by our experimental partners.
SEEK ID: https://fairdomhub.org/data_files/4211?version=1
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Pancreatic_Fibrosis_model_results.zip
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Created: 13th Aug 2021 at 16:48
Last updated: 26th Aug 2021 at 08:55
Last used: 15th May 2022 at 17:37
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https://orcid.org/0000-0003-3837-9178
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, Bio-crop, ORHIZON, Coastal Data, SASKit: Senescence-Associated Systems diagnostics Kit for cancer and stroke, hybrid sequencing, HOST-PAR, BioCreative VII, Boolean modeling of Parkinson disease map, Orphan cytochrome P450 20a1 CRISPR/Cas9 mutants and neurobehavioral phenotypes in zebrafish, Selective Destruction in Ageing, Viral Metagenomic, Synthetic biology in Synechococcus for bioeconomy applications (SynEco), testproject, SDBV ephemeral data exchanges, Test project, The BeeProject, PHENET, LiceVault, EbN1 Systems Biology
Web page: Not specified
With aging comes cellular senescence, and (multi-)morbidity. Cellular senescence is a key driver of an interconnected disease network including cancer and stroke. We wish to utilize systems modeling and bioinformatics, learning from omics and other lab data, to design and develop a biomarker + software kit with a focus on measuring and interpreting senescence-related signatures for precise (and early) diagnosis, prognosis, and, ultimately, therapy, of pancreatic cancer and ischemic stroke/thromboembolism. ...
Programme: Independent Projects
Public web page: https://www.sbi.uni-rostock.de/research/projects/detail/66
