Andreatta, Massimo

Datos académicos

PRODUCCION CIENTÍFICO TECNOLÓGICA

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Artículo Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

Andreatta, Massimo ; Karosiene, Edita; Rasmussen, Michael; Stryhn, Anette; Buus, Søren; Nielsen, Morten (Springer, 2015-09)
Artículo An automated benchmarking platform for MHC class II binding prediction methods

Andreatta, Massimo ; Trolle, Thomas; Yan, Zhen; Greenbaum, Jason A; Peters, Bjoern; Nielsen, Morten (Oxford University Press, 2018-05)
Artículo Bioinformatics tools for the prediction of T-cell epitopes

Andreatta, Massimo ; Nielsen, Morten (Springer, 2018-05)
Artículo Computational Tools for the Identification and Interpretation of Sequence Motifs in Immunopeptidomes

Alvarez, Bruno ; Barra, Carolina M. ; Nielsen, Morten ; Andreatta, Massimo (Wiley VCH Verlag, 2018-06)
Artículo Footprints of antigen processing boost MHC class II natural ligand predictions

Barra, Carolina M. ; Alvarez, Bruno ; Paul, Sinu; Sette, Alessandro; Peters, Bjoern; Andreatta, Massimo ; Buus, Søren; Nielsen, Morten (Springer Nature, 2018-11)
Artículo Gapped sequence alignment using artificial neural networks: Application to the MHC class I system

Andreatta, Massimo ; Nielsen, Morten (Oxford University Press, 2016-02-15)
Artículo GibbsCluster: unsupervised clustering and alignment of peptide sequences

Andreatta, Massimo ; Alvarez, Bruno ; Nielsen, Morten (Oxford University Press, 2017-04)
Artículo IEDB-AR: immune epitope database - analysis resource in 2019

Dhanda, Sandeep Kumar; Mahajan, Swapnil; Paul, Sinu; Yan, Zhen; Kim, Haeuk; Jespersen, Martin Closter; Jurtz, Vanessa; Andreatta, Massimo ; Greenbaum, Jason A; Marcatili, Paolo; Sette, Alessandro; Nielsen, Morten ; Peters, Bjoern (Oxford University Press, 2019-07-02)
Artículo Immunoinformatics: Predicting Peptide–MHC Binding

Nielsen, Morten ; Andreatta, Massimo ; Peters, Bjoern; Buus, Søren (Annual Review, 2020-07)
Artículo Improved methods for predicting peptide binding affinity to MHC class II molecules

Jensen, Kamilla Kjærgaard; Andreatta, Massimo ; Marcatili, Paolo; Buus, Søren; Greenbaum, Jason A.; Yan, Zhen; Sette, Alessandro; Peters, Bjoern; Nielsen, Morten (Wiley Blackwell Publishing, Inc, 2018-07)
Artículo Machine learning reveals a non‐canonical mode of peptide binding to MHC class II molecules

Andreatta, Massimo ; Jurtz, Vanessa I.; Kaever, Thomas; Sette, Alessandro; Peters, Bjoern; Nielsen, Morten (Wiley Blackwell Publishing, Inc, 2017-10)
Artículo MS-Rescue: A Computational Pipeline to Increase the Quality and Yield of Immunopeptidomics Experiments

Andreatta, Massimo ; Nicastri, Annalisa; Peng, Xu; Hancock, Gemma; Dorrell, Lucy; Ternette, Nicola; Nielsen, Morten (Wiley VCH Verlag, 2019-02)
Artículo NetH2pan: A computational tool to guide MHC peptide prediction on murine tumors

DeVette, Christa I.; Andreatta, Massimo ; Bardet, Wilfried; Cate, Steven J.; Jurtz, Vanessa I.; Jackson, Kenneth W.; Welm, Alana L.; Nielsen, Morten ; Hildebrand, William H. (American Association for Cancer Research, 2018-06)
Artículo NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length data sets

Nielsen, Morten ; Andreatta, Massimo (BioMed Central, 2016-03)
Artículo Netmhcpan-4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data

Jurtz, Vanessa; Paul, Sinu; Andreatta, Massimo ; Marcatili, Paolo; Peters, Bjoern; Nielsen, Morten (American Association of Immunologists, 2017-11)
Artículo NNAlign-MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved t-cell epitope predictions

Alvarez, Bruno ; Reynisson, Birkir; Barra, Carolina M ; Buus, Søren; Ternette, Nicola; Connelley, Tim; Andreatta, Massimo ; Nielsen, Morten (American Society for Biochemistry and Molecular Biology, 2019-10)
Artículo NNAlign: a platform to construct and evaluate artificial neural network models of receptor–ligand interactions

Nielsen, Morten ; Andreatta, Massimo (Oxford University Press, 2017-04)
Artículo Predicting HLA CD4 immunogenicity in human populations

Dhanda, Sandeep Kumar; Karosiene, Edita; Edwards, Lindy; Grifoni, Alba; Paul, Sinu; Andreatta, Massimo ; Weiskopf, Daniela; Sidney, John; Nielsen, Morten ; Peters, Bjoern; Sette, Alessandro (Frontiers Media S.A., 2018-06)
Artículo Unconventional peptide presentation by major histocompatibility complex (MHC) class i allele HLA-A∗02:01: Breaking confinement

Remesh, Soumya G.; Andreatta, Massimo ; Ying, Ge; Kaever, Thomas; Nielsen, Morten ; McMurtrey, Curtis; Hildebrand, William; Peters, Bjoern; Zajonc, Dirk M. (American Society for Biochemistry and Molecular Biology, 2017-03)

Mostrando ítems 1-19 de 19