@inbook{e28f0aafee7e4250a466718d3ba8cc1a,
title = "Machine learning methods for the protein fold recognition problem",
abstract = "The protein fold recognition problem is crucial in bioinformatics. It is usually solved using sequence comparison methods but when proteins similar in structure share little in the way of sequence homology they fail and machine learning methods are used to predict the structure of the protein. The imbalance of the data sets, the number of outliers and the high number of classes make the task very complex. We try to explain the methodology for building classifiers for protein fold recognition and to cover all the major results in this field.",
keywords = "Classifier, Features, Protein fold recognition, Supervised learning algorithm",
author = "Katarzyna Stapor and Irena Roterman-Konieczna and Piotr Fabian",
note = "Publisher Copyright: {\textcopyright} 2019, Springer International Publishing AG, part of Springer Nature.",
year = "2019",
doi = "10.1007/978-3-319-94030-4\_5",
language = "English",
series = "Intelligent Systems Reference Library",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "101--127",
booktitle = "Intelligent Systems Reference Library",
address = "Germany",
}