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Massimo Andreatta

Showing results (11-20 of 45) with videos related to

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Communications Biology|August 22, 2025
Identification of malignant cells in single-cell transcriptomics dataMassimo Andreatta, Josep Garnica, Santiago Javier Carmona
Proteomics|January 13, 2018
Computational Tools for the Identification and Interpretation of Sequence Motifs in ImmunopeptidomesBruno Alvarez, Carolina Barra, Morten Nielsen, et al.
Bioinformatics (Oxford, England)|March 8, 2022
scGate: marker-based purification of cell types from heterogeneous single-cell RNA-seq datasetsMassimo Andreatta, Ariel J Berenstein, Santiago J Carmona
Annual Review of Biomedical Data Science|July 10, 2023
Immunoinformatics: Predicting Peptide-MHC BindingMorten Nielsen, Massimo Andreatta, Bjoern Peters, et al.
Bio-Protocol|August 28, 2023
T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference MapsMassimo Andreatta, Paul Gueguen, Nicholas Borcherding, et al.
Plos One|November 5, 2010
In silico prediction of human pathogenicity in the γ-proteobacteriaMassimo Andreatta, Morten Nielsen, Frank Møller Aarestrup, et al.
Plos One|November 11, 2011
NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide dataMassimo Andreatta, Claus Schafer-Nielsen, Ole Lund, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|September 11, 2015
Quantifying Significance of MHC II ResiduesYing Fan, Ruoshui Lu, Lusheng Wang, et al.
Immunogenetics|September 30, 2015
Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identificationMassimo Andreatta, Edita Karosiene, Michael Rasmussen, et al.
Journal of Immunology (Baltimore, Md. : 1950)|October 6, 2017
NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity DataVanessa Jurtz, Sinu Paul, Massimo Andreatta, et al.
Pageof 5

Showing results (11-20 of 45) with videos related to

Sort By:
Pageof 5
Communications Biology|August 22, 2025
Identification of malignant cells in single-cell transcriptomics dataMassimo Andreatta, Josep Garnica, Santiago Javier Carmona
Proteomics|January 13, 2018
Computational Tools for the Identification and Interpretation of Sequence Motifs in ImmunopeptidomesBruno Alvarez, Carolina Barra, Morten Nielsen, et al.
Bioinformatics (Oxford, England)|March 8, 2022
scGate: marker-based purification of cell types from heterogeneous single-cell RNA-seq datasetsMassimo Andreatta, Ariel J Berenstein, Santiago J Carmona
Annual Review of Biomedical Data Science|July 10, 2023
Immunoinformatics: Predicting Peptide-MHC BindingMorten Nielsen, Massimo Andreatta, Bjoern Peters, et al.
Bio-Protocol|August 28, 2023
T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference MapsMassimo Andreatta, Paul Gueguen, Nicholas Borcherding, et al.
Plos One|November 5, 2010
In silico prediction of human pathogenicity in the γ-proteobacteriaMassimo Andreatta, Morten Nielsen, Frank Møller Aarestrup, et al.
Plos One|November 11, 2011
NNAlign: a web-based prediction method allowing non-expert end-user discovery of sequence motifs in quantitative peptide dataMassimo Andreatta, Claus Schafer-Nielsen, Ole Lund, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|September 11, 2015
Quantifying Significance of MHC II ResiduesYing Fan, Ruoshui Lu, Lusheng Wang, et al.
Immunogenetics|September 30, 2015
Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identificationMassimo Andreatta, Edita Karosiene, Michael Rasmussen, et al.
Journal of Immunology (Baltimore, Md. : 1950)|October 6, 2017
NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity DataVanessa Jurtz, Sinu Paul, Massimo Andreatta, et al.
Pageof 5