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HIV-1 cleavage prediction

This repository contains the notebook and the report for the course of Machine Learning for Physicists, held at the TU Dortmund in the academic year of 2022/2023.

The idea of the project is based on the paper by Onah and colleagues (https://doi.org/10.1186/s12859-022-05017-x). The code consists in the implementation of some supervised learning algorithms for predicting the clavage site in Gag and Gag-Pol polyproteins by HIV-1 protease, which is a fundamental step for the replication of HIV. Understanding and predicting the cleavage site can help in the development of drugs against HIV.

Before launching the code, save the .xlsx file containing the data in your Google Drive home page.