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arXiv · 2311.17521

Spinal Muscle Atrophy Disease Modelling as Bayesian Network

Mohammed Ezzat Helal·Manal Ezzat Helal·Sherif Fadel Fahmy
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Abstract

We investigate the molecular gene expressions studies and public databases for disease modelling using Probabilistic Graphical Models and Bayesian Inference. A case study on Spinal Muscle Atrophy Genome-Wide Association Study results is modelled and analyzed. The genes up and down-regulated in two stages of the disease development are linked to prior knowledge published in the public domain and co-expressions network is created and analyzed. The Molecular Pathways triggered by these genes are identified. The Bayesian inference posteriors distributions are estimated using a variational analytical algorithm and a Markov chain Monte Carlo sampling algorithm. Assumptions, limitations and possible future work are concluded.

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Mohammed Ezzat Helal, Manal Ezzat Helal, Sherif Fadel Fahmy. 2023-11-29. Spinal Muscle Atrophy Disease Modelling as Bayesian Network. https://doi.org/10.1088/1742-6596%2F2128%2F1%2F012015

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