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Massimo Andreatta

Showing results (1-10 of 45) with videos related to

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Bioinformatics (Oxford, England)|October 31, 2015
Gapped sequence alignment using artificial neural networks: application to the MHC class I systemMassimo Andreatta, Morten Nielsen
Genome Medicine|April 1, 2016
NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasetsMorten Nielsen, Massimo Andreatta
Immunology|February 23, 2012
Characterizing the binding motifs of 11 common human HLA-DP and HLA-DQ molecules using NNAlignMassimo Andreatta, Morten Nielsen
Nucleic Acids Research|April 14, 2017
NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactionsMorten Nielsen, Massimo Andreatta
Methods in Molecular Biology (Clifton, N.J.)|May 2, 2018
Bioinformatics Tools for the Prediction of T-Cell EpitopesMassimo Andreatta, Morten Nielsen
Bioinformatics (Oxford, England)|August 27, 2020
STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq dataMassimo Andreatta, Santiago J Carmona
Computational and Structural Biotechnology Journal|July 21, 2021
UCell: Robust and scalable single-cell gene signature scoringMassimo Andreatta, Santiago J Carmona
Bioinformatics (Oxford, England)|February 10, 2026
UCell and pyUCell: single-cell gene signature scoring for R and pythonMassimo Andreatta, Santiago J Carmona
Nucleic Acids Research|April 14, 2017
GibbsCluster: unsupervised clustering and alignment of peptide sequencesMassimo Andreatta, Bruno Alvarez, Morten Nielsen
Bioinformatics (Oxford, England)|October 26, 2012
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approachMassimo Andreatta, Ole Lund, Morten Nielsen
Pageof 5

Showing results (1-10 of 45) with videos related to

Sort By:
Pageof 5
Bioinformatics (Oxford, England)|October 31, 2015
Gapped sequence alignment using artificial neural networks: application to the MHC class I systemMassimo Andreatta, Morten Nielsen
Genome Medicine|April 1, 2016
NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasetsMorten Nielsen, Massimo Andreatta
Immunology|February 23, 2012
Characterizing the binding motifs of 11 common human HLA-DP and HLA-DQ molecules using NNAlignMassimo Andreatta, Morten Nielsen
Nucleic Acids Research|April 14, 2017
NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactionsMorten Nielsen, Massimo Andreatta
Methods in Molecular Biology (Clifton, N.J.)|May 2, 2018
Bioinformatics Tools for the Prediction of T-Cell EpitopesMassimo Andreatta, Morten Nielsen
Bioinformatics (Oxford, England)|August 27, 2020
STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq dataMassimo Andreatta, Santiago J Carmona
Computational and Structural Biotechnology Journal|July 21, 2021
UCell: Robust and scalable single-cell gene signature scoringMassimo Andreatta, Santiago J Carmona
Bioinformatics (Oxford, England)|February 10, 2026
UCell and pyUCell: single-cell gene signature scoring for R and pythonMassimo Andreatta, Santiago J Carmona
Nucleic Acids Research|April 14, 2017
GibbsCluster: unsupervised clustering and alignment of peptide sequencesMassimo Andreatta, Bruno Alvarez, Morten Nielsen
Bioinformatics (Oxford, England)|October 26, 2012
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approachMassimo Andreatta, Ole Lund, Morten Nielsen
Pageof 5