Author(s):
Sequeira, Ana ; Lousa, Diana ; Rocha, Miguel
Date: 2021
Persistent ID: https://hdl.handle.net/1822/74506
Origin: RepositóriUM - Universidade do Minho
Subject(s): Bioinformatics; Ontologies; Cancer; Machine learning; Protein/Peptide classification; Python package
Description
A challenging problem in Bioinformatics is to predict protein structure, properties, activities or interactions from their aminoacid sequences. Sequence-derived physicochemical features of proteins have been used to support the development of Machine Learning (ML) models. However, tools and platforms to calculate features from protein sequences and train ML models are scarce and have limitations in terms of performance, user-friendliness and domains of application.