SOURCE-LINKED INTELLIGENCE

Integrated Mechanistic Modelling and Analysis of Large-scale Biomedical Data

CORDIS · observation · Publication date unknown

signalling processes in cancer, ranging from model development to parameterisation all the way to uncertainty analysis. To this end, I will combine methods from the fields of mathematical modelling, machine learning, and signal processing with established approaches in systems biology. The model development will employ natural language processing and an automatic testing framework. For federated model inference, I will develop scalable mini-batch optimisation and marginalisation based uncertainty quantification. To refine models, I will exploit tools from signal processing, such as blind identification of latent variables. I will apply the developed scalable mechanistic modelling approach to integrate large-scale biomedical data for molecular phenotyping studies and clinical trials across sites. This will provide mechanistic models reconciling the available data. The study will, for the first time, combine mechanistic modelling and machine learning for the integrated analysis of patient-derived omics and phenotypic data. By linking these data sources, INTEGRATE will deepen our unde

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recordType

award

status

SIGNED

region

EU

value

1854546

unit

EUR