Heider, Dominik; Hoffmann, Daniel:
Interpol : An R package for preprocessing of protein sequences
In: BioData Mining, Band 4 (2011), S. 16
2011Artikel/Aufsatz in ZeitschriftOA Gold
MedizinBiologieForschungszentren » Zentrum für Medizinische Biotechnologie (ZMB)Fakultät für Biologie » Bioinformatics and Computational Biophysics
Damit verbunden: 1 Publikation(en)
Titel in Englisch:
Interpol : An R package for preprocessing of protein sequences
Autor*in:
Heider, DominikUDE
LSF ID
50610
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Hoffmann, DanielUDE
GND
1214304125
LSF ID
16263
ORCID
0000-0003-2973-7869ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
Erscheinungsjahr:
2011
Open Access?:
OA Gold
DuEPublico 1 ID
Notiz:
OA Förderung 2011
Sprache des Textes:
Englisch

Abstract in Englisch:

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.