PathoAnalyzer-I: Python Code, Datasets, and User Guide for Deciphering Chronic Diseases

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Authors: Ali Aguerd, Faiza Bennis, Fatima Chegdani
Cited by: 0

Abstract

PathoAnalyzer-I is a computational platform that integrates machine learning and bioinformatics approaches to decipher chronic diseases. This repository provides the complete project files required to run the platform. The archive PathoAnalyzer-I.7z contains the following components: datasetTSV files containing curated data related to 531 pathologies, including genetic and molecular information used by the platform. deciphering_incurable_pathologiesCore Python scripts required to run the PathoAnalyzer-I platform. requirements.txtList of Python libraries required to install and execute the program. PredictionScripts used to build and apply machine-learning models for genetic prediction tasks: RiskAllele-Prediction – model training and prediction of risk alleles SNP-Prediction – model training and prediction of SNPs associated with diseases ValidationTwo Python scripts used to validate the performance of the prediction models. User GuideA user manual (Word document) describing the installation steps and the use of the platform’s functionalities.

Fields of Study & Subjects

Genetic Associations and Epidemiology Genomics and Rare Diseases Bioinformatics and Genomic Networks

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 March 2026
Language
EN