Data integration in logic-based models of biological mechanisms

Benjamin A Hall (1) , Anna Niarakis (2, 3, 4)

1 UCL - University College of London [London]
2 Génopole [Evry]
3 Lifeware - Computational systems biology and optimization
4 GenHotel - Laboratoire de recherche européen pour la polyarthrite rhumatoïde

Discrete, logic-based models are increasingly used to describe biological mechanisms. Initially introduced to study gene regulation, these models evolved to cover various molecular mechanisms, such as signaling, transcription factor cooperativity, and even metabolic processes. The abstract nature and amenability of discrete models to robust mathematical analyses make them appropriate for addressing a wide range of complex biological problems. Recent technological breakthroughs have generated a wealth of high-throughput data. Novel, literature-based representations of biological processes and emerging algorithms offer new opportunities for model construction. Here, we review up-to-date efforts to address challenging biological questions by incorporating omic data into logic-based models and discuss critical difficulties in constructing and analyzing integrative, large-scale, logicbased models of biological mechanisms.

Mots clés: Logic-based models; Boolean models; Executable models; Qualitative dynamical modeling; Omic data integration; In silico simulations; Formal verification

Domaines: Bio-informatique [q-bio.QM]

Benjamin A Hall, Anna Niarakis. Data integration in logic-based models of biological mechanisms. Current Opinion in Systems Biology, 2021, 28, pp.100386. ⟨10.1016/j.coisb.2021.100386⟩. ⟨hal-03515653⟩