/CBP-Project

Primary LanguagePython

COMPUTATIONAL BIOPHYSICS PROJECT

Project Title: Identification of Disease-Associated Genes using ML

Requirements

  1. Scikit-learn
  2. Pandas
  3. Numpy
  4. Matplotlib
  5. Tensorflow

Files

  1. disgenet_2020.db: Database file of DisGeNET (this file should be downloaded in the root directory from the DisGeNET website)
  2. gene_sequences_final.{csv, fasta}: Gene sequences to be used in training downloaded from NCBI
  3. model.py: Contains the code for training the model using traditional ML algorithms
  4. model_neural.py: Contains the code for training the model using neural networks
  5. features/ : directory containing the feature vectors for the seuqences in gene_sequences_final.csv
  6. model_pca_10/ : directory containing the trained models using PCA with 10 components
  7. model_pca_20/ : directory containing the trained models using PCA with 20 components
  8. model_neural/ : directory containing the trained neural network model
  9. results/ : directory containing the results of the models