Heider, Dominik; Hoffmann, Daniel:
Interpol: An R package for preprocessing of protein sequences
2011
In: BioData Mining, Band 4 (2011), S. 16
Artikel/Aufsatz in Zeitschrift / Fach: Informatik; Biologie
Fakultät für Biologie
Titel:
Interpol: An R package for preprocessing of protein sequences
Autor(in):
Heider, Dominik im Online-Personal- und -Vorlesungsverzeichnis LSF anzeigen; Hoffmann, Daniel im Online-Personal- und -Vorlesungsverzeichnis LSF anzeigen
Erscheinungsjahr:
2011
Erschienen in:
BioData Mining, Band 4 (2011), S. 16
Link URL:
Link URL:

Abstract:

Background: Most machine learning techniques currently applied in the literature need a fixed dimensionality of input data. However, this requirement is frequently violated by real input data, such as DNA and protein sequences, that often differ in length due to insertions and deletions. It is also notable that performance in classification and regression is often improved by numerical encoding of amino acids, compared to the commonly used sparse encoding. Results: The software "Interpol" encodes amino acid sequences as numerical descriptor vectors using a database of currently 532 descriptors (mainly from AAindex), and normalizes sequences to uniform length with one of five linear or non-linear interpolation algorithms. Interpol is distributed with open source as platform independent R-package. It is typically used for preprocessing of amino acid sequences for classification or regression. Conclusions: The functionality of Interpol widens the spectrum of machine learning methods that can be applied to biological sequences, and it will in many cases improve their performance in classification and regression.