Protein alignment based on higher order conditional random fields for template-based modeling Morales Cordovilla, Juan Andrés Sánchez Calle, Victoria Eugenia Ratajczak, Martin 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. 2019-08-08T09:44:49Z 2019-08-08T09:44:49Z 2018-06-01 info:eu-repo/semantics/article Morales-Cordovilla JA, Sanchez V, RatajczakM (2018) Protein alignment based on higher order conditional random fields for template-based modeling. PLoS ONE 13(6): e0197912. [https://doi.org/10.1371/journal. pone.0197912] http://hdl.handle.net/10481/56610 10.1371/journal. pone.0197912 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España Public Library of Science (PLOS)