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PerMedCoE webinar: Logic modelling of signalling networks - CellNOpt and CARNIVAL
The PerMedCoE webinar series aims to present and discuss topics and best practices in the field of personalized medicine. All PerMedCoE webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing.

Abstract:
Reconstruction of signaling networks has been widely utilised in the past, for example to understand aberrations in diseased cells, or to figure out mechanism of drug actions. With the development of high throughput data platforms, it is possible to infer these networks from the data alone, alternatively we could reuse existing knowledge about possible mechanisms reported in literature and interaction databases. The prior knowledge network (PKN) describes the possible interactions among the signaling molecules and connects the perturbations to the measured molecular markers. Different formalisms build different types of models from the PKN, ranging from boolean networks to differential equations. It is then possible to train the models to the measured data using optimisation methods. CellNOpt uses different logic formalisms, which include boolean, fuzzy, probabilistic, and ordinary differential equations models which are trained against (phosphoproteomic) data. On the other hand, similar approaches are used to extract mechanistic insights from multi-omics data using CARNIVAL to train signaling networks from gene expression data using integer linear programming to infer causal paths linking signaling drives with downstream transcripts’ levels. In this webinar, we introduce CellNOpt and CARNIVAL and show how each can be used to build models of signalling networks.

Speaker: Pablo Rodríguez Mier, Joint Research-Center for Computational Biomedicine

Jan 20, 2022 03:00 PM in Brussels

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