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Predicting the Start of Protein α-Helices Using Machine Learning Algorithms

  • Rui Camacho
  • Rita Ferreira
  • Natacha Rosa
  • Vânia Guimarães
  • Nuno A. Fonseca
  • Vítor Santos Costa
  • Miguel de Sousa
  • Alexandre Magalhães
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 74)

Introduction

Proteins are complex structures synthesised by living organisms. They are actually a fundamental type of molecules and can perform a large number of functions in cell biology. Proteins can assume catalytic roles and accelerate or inhibit chemical reactions in our body. They can assume roles of transportation of smaller molecules, storage, movement, mechanical support, immunity and control of cell growth and differentiation [25]. All of these functions rely on the 3D-structure of the protein. The process of going from a linear sequence of amino acids, that together compose a protein, to the protein’s 3D shape is named protein folding. Anfinsen’s work [29] has proven that primary structure determines the way protein folds. Protein folding is so important that whenever it does not occur correctly it may produce diseases such as Alzheimer’s, Bovine Spongiform Encephalopathy (BSE), usually known as mad cows disease, Creutzfeldt-Jakob (CJD) disease, a Amyotrophic Lateral Sclerosis (ALS), Huntingtons syndrome, Parkinson disease, and other diseases related to cancer.

Keywords

Secondary Structure Amyotrophic Lateral Sclerosis Bovine Spongiform Encephalopathy Machine Learn Algorithm Inductive Logic Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Rui Camacho
    • 1
  • Rita Ferreira
    • 1
  • Natacha Rosa
    • 1
  • Vânia Guimarães
    • 1
  • Nuno A. Fonseca
    • 2
  • Vítor Santos Costa
    • 2
    • 3
  • Miguel de Sousa
    • 4
  • Alexandre Magalhães
    • 4
  1. 1.LIAAD & Faculdade de Engenharia da Universidade do PortoPortugal
  2. 2.CRACS-INESC PortoPortugal
  3. 3.DCC-Faculdade de Ciências da Universidade do PortoPortugal
  4. 4.REQUIMTE/Faculdade de Ciências da Universidade do PortoPortugal

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