A Bayesian Network Model for the Parkinson’s Disease: A Study of Gene Expression Levels

  • Sonia Lilia Mestizo-GutiérrezEmail author
  • Joan Arturo Jácome-Delgado
  • Viviana Yarel Rosales-Morales
  • Nicandro Cruz-Ramírez
  • Gonzalo Emiliano Aranda-Abreu
Part of the Studies in Computational Intelligence book series (SCI, volume 815)


Parkinson’s disease (PD) is a neurodegenerative disorder characterized by tremor, postural instability, bradykinesia and rigidity. It is the second most prevalent neurodegenerative disease in the world. Currently, no cure has been found. Multiple investigations have proposed environmental and genetic factors, but no one has been determined as the trigger for the development of this disease, so it is a public health challenge in our society characterized by the increase of elderly people. The use of machine learning techniques has increased in the medical field and to help solve biological problems. The unprecedented volume of biomedical data provides a great opportunity for better understanding, prediction and decision making of conditions. In this study, we modeled gene expression profiles of peripheral blood samples from 105 individuals (50 with PD, 33 with control of neurodegenerative diseases, other than PD, and 22 healthy controls) using Bayesian networks with different dimensionality reduction techniques to create several sets of genes. From the obtained sets, classification models were generated and some genes that could be considered as PD candidates were obtained and some genes previously reported with this disease were corroborated.


Parkinson’s disease Bayesian network Gene expression levels Microarray 



The authors thankfully acknowledge the computer resources, technical expertise and support provided by the Laboratorio Nacional de Supercómputo del Sureste de México, CONACYT network of national laboratories.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sonia Lilia Mestizo-Gutiérrez
    • 1
    Email author
  • Joan Arturo Jácome-Delgado
    • 2
  • Viviana Yarel Rosales-Morales
    • 3
  • Nicandro Cruz-Ramírez
    • 3
  • Gonzalo Emiliano Aranda-Abreu
    • 4
  1. 1.Facultad de Ciencias QuímicasUniversidad VeracruzanaXalapaMexico
  2. 2.Laboratorio Nacional de Informática AvanzadaXalapaMéxico
  3. 3.Centro de Investigación en Inteligencia ArtificialUniversidad VeracruzanaXalapaMéxico
  4. 4.Centro de Investigaciones CerebralesUniversidad VeracruzanaXalapaMéxico

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