nmercadeb / Computational-Biophysics-project

Codes for the final project of the subject Computational Biophysics of the degree Engineering Physics (UPC). By Marta Alcalde i Núria Mercadé.

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Computational-Biophysics-project

Codes for the final project of the subject Computational Biophysics of the degree Engineering Physics (UPC). By Marta Alcalde i Núria Mercadé.

Briew code description:

  • AnovaNOStroke: this code analyses by means of Anova statistics test the data of mice that do not present stroke in the different test performances.
  • AnovaTest: in this code is used once again the Anova test, this time to find significant differences between non stroke and stroke groups, and also among the non stroke and the stroke group divided in mild and severe stroke.
  • PearsonCorrelation: in this code the Pearson Correlation test to see whether the different features of the dataset present correlation with the brain injury degree.
  • GNB: the Gaussian Naive Bayes prediction algorithm is used to predict whether a mouse has or not stroke.
  • KNC: the K - Neighbors Classifier prediction algorithm is used to predict whether a mouse has or not stroke.
  • LR: the Logistic Regression prediction algorithm is used to predict whether a mouse has or not stroke.
  • RF: the Random Forest prediction algorithm is used to predict whether a mouse has or not stroke.
  • SVM: the Support Vector Machine prediction algorithm is used to predict whether a mouse has or not stroke.

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Codes for the final project of the subject Computational Biophysics of the degree Engineering Physics (UPC). By Marta Alcalde i Núria Mercadé.


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