Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/67119
Author(s): | Rui Camacho Rita Ferreira Natacha Rosa Vânia Guimarães Nuno A Fonseca Vítor Santos Costa Miguel de Sousa Alexandre Magalhaes |
Title: | Predicting the secondary structure of proteins using Machine Learning algorithms |
Issue Date: | 2012 |
Abstract: | The functions of proteins in living organisms are related to their 3-D structure, which is known to be ultimately determined by their linear sequence of amino acids that together form these macromolecules. It is, therefore, of great importance to be able to understand and predict how the protein 3D-structure arises from a particular linear sequence of amino acids. In this paper we report the application of Machine Learning methods to predict, with high values of accuracy, the secondary structure of proteins, namely alpha-helices and beta-sheets, which are intermediate levels of the local structure. |
Subject: | Matemática Mathematics |
Scientific areas: | Ciências exactas e naturais::Matemática Natural sciences::Mathematics |
URI: | https://repositorio-aberto.up.pt/handle/10216/67119 |
Document Type: | Artigo em Revista Científica Internacional |
Rights: | openAccess |
License: | https://creativecommons.org/licenses/by-nc/4.0/ |
Appears in Collections: | FCUP - Artigo em Revista Científica Internacional FEUP - Artigo em Revista Científica Internacional |
Files in This Item:
File | Description | Size | Format | |
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57762.pdf | Predicting the secondary structure of proteins using Machine Learning algorithms | 1.47 MB | Adobe PDF | View/Open |
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