@misc{10481/56610,
year = {2018},
month = {6},
url = {http://hdl.handle.net/10481/56610},
abstract = {The query-template alignment of proteins is one of the most critical steps of template-based
modeling methods used to predict the 3D structure of a query protein. This alignment can be
interpreted as a temporal classification or structured prediction task and first order Conditional
Random Fields have been proposed for protein alignment and proven to be rather
successful. Some other popular structured prediction problems, such as speech or image
classification, have gained from the use of higher order Conditional Random Fields due to
the well known higher order correlations that exist between their labels and features. In this
paper, we propose and describe the use of higher order Conditional Random Fields for
query-template protein alignment. The experiments carried out on different public datasets
validate our proposal, especially on distantly-related protein pairs which are the most difficult
to align.},
organization = {This research was supported by Project
P12.TIC.1485 funded by Consejeria de Economia,
Innovacion y Ciencia (Junta de Andalucia) and
Spanish MINECO/FEDER Project TEC2016-80141-
P.},
publisher = {Public Library of Science (PLOS)},
title = {Protein alignment based on higher order conditional random fields for template-based modeling},
doi = {10.1371/journal. pone.0197912},
author = {Morales Cordovilla, Juan Andrés and Sánchez Calle, Victoria Eugenia and Ratajczak, Martin},
}