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VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
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DTSTAMP:20260717T145401Z
UID:c5c2b88e-9fa9-4458-a5a9-de2e8d1212f8
DTSTART:20231212T090000Z
DTEND:20231212T170000Z
DESCRIPTION:Cellular signalling networks are the communication pathways tha
 t govern the behaviour of cells. They allow cells to receive and process e
 xternal signals\, such as growth factors and hormones\, and respond approp
 riately by activating specific gene expression programs or inducing cellul
 ar behaviours like proliferation\, migration\, and differentiation. Disrup
 tions in these signalling networks can lead to various diseases\, includin
 g cancer\, metabolic disorders\, and immune disorders. Understanding the r
 egulatory mechanisms of signalling networks is critical to developing effe
 ctive therapies for these diseases.\n\nOne approach to discover signalling
  network alterations from omics data is through the use of upstream regula
 tory pathway analysis\, which aims to identify the transcription factors a
 nd upstream signalling regulators that control the expression of downstrea
 m genes. This can be achieved through the joint analysis of omics data and
  the signalling network structure using methods such as CARNIVAL. By using
  powerful algorithms and general purpose integer optimization solvers\, CA
 RNIVAL explores the vast space of potential signalling alterations to iden
 tify a parsimonious signalling network that explains the measurements.\n\n
 In this course\, participants will learn how to process differential gene 
 expression data to estimate transcription factor activities with [Decoupl
 eR](https://saezlab.github.io/decoupleR/)\, obtain and process prior knowl
 edge networks with [OmniPath](https://omnipathdb.org/) and [pypath](htt
 ps://github.com/saezlab/pypath)\, and use [CARNIVAL](https://saezlab.gith
 ub.io/CARNIVAL/) to infer signalling networks.\n\n 
SUMMARY:From transcriptomics to mechanistic models of signalling
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/transcriptomics-mechani
 stic-models-signalling-Dec2023
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