Unsupervised learning methods to Identify essential genes associated with SARS-CoV-2
Descripotion:
This repository contains the data and MATLAB code for the "Identifying essential genes associated with SARS-CoV-2 as potential drug target candidates with machine learning algorithms":
Data sets:
File "Process related to 332 proteins.xlsx" contains 1,374 informative biological processes related to COVID-19 that are published on the Gene Ontology.
File "List_Protein_Name.mat" is the MATLAB .mat file contains the list of 20,040 proteins which are analyzed.
File "Feature_Matrix.mat" is the MATLAB that contains informative features for 20,040 proteins from inputs related to COVID-19
To run an algorithm "Topological_feature.m".
To run three machine learning algorithms follow the "Read_me.txt" steps.