Martínez Naves, EduardoReche Gallardo, Pedro AntonioLafuente Duarte, María Esther2023-06-202023-06-202011Martínez Naves, E., Reche Gallargo, P. A. & Lafuente Duarte, M. E. et al. «Recognition of the Ligand-Type Specificity of Classical and Non-Classical MHC I Proteins». FEBS Letters, vol. 585, n.o 21, noviembre de 2011, pp. 3478-84. DOI.org (Crossref), https://doi.org/10.1016/j.febslet.2011.10.007.1873-346810.1016/j.febslet.2011.10.007https://hdl.handle.net/20.500.14352/41998Functional characterization of proteins belonging to the MHC I superfamily involves knowing their cognate ligands, which can be peptides, lipids or none. However, the experimental identification of these ligands is not an easy task and generally requires some a priori knowledge of their chemical nature (ligand-type specificity). Here, we trained k-nearest neighbor and support vector machine classifiers that predict the ligand-type specificity MHC I proteins with great accuracy. Moreover, we applied these classifiers to human and mouse MHC I proteins of uncharacterized ligands, obtaining some results that can be instrumental to unravel the function of these proteins.engAtribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/journal articlehttps//doi.org/10.1016/j.febslet.2011.10.007http://www.sciencedirect.com/science/article/pii/S0014579311007459open access577.257:004Classical MHC class I moleculeNon-classical MHC class I moleculeMachine learningLigandPredictionBiología molecular (Biología)Bioinformática2415 Biología Molecular