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UID:9135@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20260521T170000
DTEND;TZID=Europe/Paris:20260521T174500
DTSTAMP:20260625T180411Z
URL:https://www.i2m.univ-amu.fr/evenements/automated-construction-of-boole
 an-models-using-knowledge-graphs/
SUMMARY:Nina Alger (I2M): Automated construction of Boolean models using kn
 owledge graphs
DESCRIPTION:Nina Alger: Abstract : Boolean modeling has emerged as a power
 ful qualitative formalism to study the dynamics of gene regulatory network
 s\, and in particular in cancer. A Boolean model (BM) consists of a Regula
 tory graph (RG) — a signed directed graph capturing regulatory interacti
 ons — coupled with a set of logical rules\, called network parametrizati
 on\, that govern the activation state of each node. By simulating these dy
 namics\, BMs predict the network's evolution through various functional st
 ates in response to different environmental conditions.\n\n\n\nHowever\, c
 onstructing the RG remains a time-consuming and largely manual process due
  to the large amount of heterogeneous data available. Here\, we present an
  automated pipeline for RG construction and BM inference.\n\nFirst\, a kno
 wledge graph (KG) is assembled by integrating multiple prior knowledge dat
 abases using OntoWeaver and BioCypher: protein-protein interactions and pa
 thways (OmniPath)\, drug-target interactions (OpenTargets)\, cancer gene b
 iomarkers (OncoKB)\, and tissue-specific gene expression (Human Protein At
 las). Each database is integrated via dedicated Ontoweaver adapters\, and 
 BioCypher harmonizes the chosen ontology. Then\, a context-specific subset
  of proteins is extracted from the KG with user-defined biological queries
 . Tools such as NeKo are then used for network parametrization thereby bui
 lding the RG for the BM with this subset of proteins.\n\nThe approach is b
 enchmarked against the manually constructed BM of Flobak et al. (2015) on 
 AGS gastric cancer cells\, assessing whether the automated network recapit
 ulates the same drug synergy predictions. Automating PKN construction is a
  step toward personalized BM integrating patient-specific omics data.\n\n
CATEGORIES:Séminaire,Rencontres doctorant⋅es I2M-CPT
LOCATION:I2M Luminy - TPR2\, Salle de Séminaire 304-306 (3ème étage)\, 1
 63 Avenue de Luminy\, Marseille\, 13009\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=163 Avenue de Luminy\, Mars
 eille\, 13009\, France;X-APPLE-RADIUS=100;X-TITLE=I2M Luminy - TPR2\, Sall
 e de Séminaire 304-306 (3ème étage):geo:0,0
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DTSTART:20260329T030000
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