Spinal Muscle Atrophy Disease Modelling as Bayesian Network
- URL: http://arxiv.org/abs/2311.17521v1
- Date: Wed, 29 Nov 2023 10:45:27 GMT
- Title: Spinal Muscle Atrophy Disease Modelling as Bayesian Network
- Authors: Mohammed Ezzat Helal, Manal Ezzat Helal, Sherif Fadel Fahmy
- Abstract summary: 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.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- 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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