Boolean modelling as a logic-based dynamic approach in systems medicine

Hemedan, Ahmed Abdelmonem; Niarakis, Anna; Schneider, Reinhard; Ostaszewski, Marek

doi:10.1016/j.csbj.2022.06.035

Cited by 38 publications

(32 citation statements)

References 123 publications

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“…Boolean networks describe regulatory interactions over time using Boolean variables as the states of genes and Boolean functions to determine the current gene states as a function of the previous states of other genes [113] . In a Boolean network, the expression of each gene is discretized to only “on” (expressed) or “off” (not expressed).…”

Section: Gene Regulatory Network Inferencementioning

confidence: 99%

Network-based approaches for modeling disease regulation and progression

Galindez

Sadegh

Baumbach

et al. 2023

Computational and Structural Biotechnology Journal

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Section: Gene Regulatory Network Inferencementioning

confidence: 99%

Network-based approaches for modeling disease regulation and progression

Galindez

Sadegh

Baumbach

et al. 2023

Computational and Structural Biotechnology Journal

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“…The behavior of the output biomolecules is described by Boolean functions (BFs) that define the interactions between the inputs. Updating schemes determine the order in which BFs are calculated (Hemedan et al (2022)). BFs have been primarily used to describe gene regulation, but they have also been applied to signaling networks using various logical formalisms, including Boolean, differential, and fuzzy equations (Terfve (2012); Bloomingdale (2018); Eduati (2020)).…”

Section: Introductionmentioning

confidence: 99%

Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses

Hemedan

Schneider

Ostaszewski

2023

Preprint

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Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson's disease (PD), one of the most prevalent neurodegenerative disorders. Our approach is based on the PD-map, a comprehensive molecular interaction diagram that captures the key mechanisms involved in the initiation and progression of PD. Using Boolean modeling, we aim to gain a deeper understanding of the disease dynamics, identify potential drug targets, and simulate the response to treatments. Our analysis demonstrates the effectiveness of this approach in uncovering the intricacies of PD. Our results confirm existing knowledge about the disease and provide valuable insights into the underlying mechanisms, ultimately suggesting potential targets for therapeutic intervention. Moreover, our approach allows us to parametrize the models based on omics data for further disease stratification. Our study highlight the value of computational modeling in advancing our understanding of complex biological systems and diseases, emphasizing the importance of continued research in this field. Furthermore, our findings have potential implications for the development of novel therapies for PD, which is a pressing public health concern. Overall, this study represents a significant step forward in the application of computational modeling to the investigation of neurodegenerative diseases, and underscores the power of interdisciplinary approaches in tackling challenging biomedical problems.

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“…Discrete logic-based qualitative modelling has been increasingly used to model largescale networks for which kinetic data is scarce (Hemedan et al, 2022;Hall & Niarakis, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Discrete logic-based qualitative modelling has been increasingly used to model large-scale networks for which kinetic data is scarce (Hemedan et al , 2022; Hall & Niarakis, 2021). For example, in a Boolean model, each node can take only two values, 0 (FALSE) and 1 (TRUE).…”

Section: Introductionmentioning

confidence: 99%

A large-scale Boolean model of the Rheumatoid Arthritis Fibroblast-Like Synoviocytes predicts drug synergies in the arthritic joint

Singh

Naldi

Soliman

et al. 2023

Preprint

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Rheumatoid arthritis (RA) is a complex autoimmune disease with an unknown aetiology. However, rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS) play a significant role in initiating and perpetuating destructive joint inflammation by expressing immuno-modulating cytokines, adhesion molecules, and matrix remodelling enzymes. In addition, RA-FLS are primary drivers of inflammation, displaying high proliferative rates and an apoptosis-resistant phenotype. Thus, RA-FLS-directed therapies could become a complementary approach to immune-directed therapies by predicting the optimal conditions that would favour RA-FLS apoptosis, limit inflammation, slow the proliferation rate and minimise bone erosion and cartilage destruction. In this paper, we present a large-scale Boolean model for RA-FLS that consists of five submodels focusing on apoptosis, cell proliferation, matrix degradation, bone erosion and inflammation. The five phenotype-specific submodels can be simulated independently or as a global model. In-silico simulations and perturbations reproduced the expected biological behaviour of the system under defined initial conditions and input values. The model was then used to mimic the effect of mono or combined therapeutic treatments and predict novel targets and drug candidates through drug repurposing analysis.

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Boolean modelling as a logic-based dynamic approach in systems medicine

Cited by 38 publications

References 123 publications

Network-based approaches for modeling disease regulation and progression

Network-based approaches for modeling disease regulation and progression

Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses

A large-scale Boolean model of the Rheumatoid Arthritis Fibroblast-Like Synoviocytes predicts drug synergies in the arthritic joint

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