Paolo Marcatili

发表

NetSurfP-2.0: improved prediction of protein structural features by integrated deep learning

Ole Winther, Michael Schantz Klausen, Martin Closter Jespersen, 2018, bioRxiv.

MAISTAS: a tool for automatic structural evaluation of alternative splicing products

Massimiliano Orsini, Paolo Marcatili, Matteo Floris, 2011, Bioinform..

T-Cell Receptor Cognate Target Prediction Based on Paired α and β Chain Sequence and Structural CDR Loop Similarities

Paolo Marcatili, Esteban Lanzarotti, Morten Nielsen, 2019, Front. Immunol..

Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server

Paolo Marcatili, Anna Tramontano, Pier Paolo Olimpieri, 2013, Bioinform..

PIGS: automatic prediction of antibody structures

Paolo Marcatili, Anna Tramontano, Alessandra Rosi, 2008, Bioinform..

TCRpMHCmodels: Structural modelling of TCR-pMHC class I complexes

Bjoern Peters, Martin Closter Jespersen, Paolo Marcatili, 2019, Scientific Reports.

The MoVIN server for the analysis of protein interaction networks

Paolo Marcatili, Anna Tramontano, Giovanni Bussotti, 2008, BMC Bioinformatics.

LYRA, a webserver for lymphocyte receptor structural modeling

Michael Schantz Klausen, Martin Closter Jespersen, Morten Nielsen, 2015, Nucleic Acids Res..

Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity

Andrea Pagnani, Paolo Marcatili, Guido Uguzzoni, 2016, PLoS Comput. Biol..

Improving the accuracy of the structure prediction of the third hypervariable loop of the heavy chains of antibodies

Paolo Marcatili, Anna Tramontano, Rosalba Lepore, 2014, Bioinform..

BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes

Bjoern Peters, Martin Closter Jespersen, Morten Nielsen, 2017, Nucleic Acids Res..

Automated Clustering Analysis of Immunoglobulin Sequences in Chronic Lymphocytic Leukemia Based on 3D Structural Descriptors

Dimitrios Tzovaras, Panagiotis Moschonas, Paolo Marcatili, 2016 .

T cell receptor sequence clustering and antigen specificity

Paolo Marcatili, Joseph Kaplinsky, Thomas Lars Andresen, 2020, Computational and structural biotechnology journal.

Stereotyped patterns of B-cell receptor in splenic marginal zone lymphoma

Anna Tramontano, Francesco Bertoni, Paolo Marcatili, 2010, Haematologica.

Erratum: Antibody structural modeling with prediction of immunoglobulin structure (PIGS) (Nature Protocols (2014) 9 (2771-2783) DOI: 10.1038/nprot.2014.189)

Anna Tramontano, Paolo Marcatili, Pier Paolo Olimpieri, 2015 .

Epitope Specific Antibodies and T Cell Receptors in the Immune Epitope Database

Morten Nielsen, Bjoern Peters, Alessandro Sette, 2018, Front. Immunol..

The association of heavy and light chain variable domains in antibodies: implications for antigen specificity

Anna Tramontano, Paolo Marcatili, Anna Chailyan, 2011, The FEBS journal.

T cell receptor fingerprinting enables in-depth characterization of the interactions governing recognition of peptide–MHC complexes

Morten Nielsen, Paolo Marcatili, Sine R Hadrup, 2018, Nature Biotechnology.

Igs Expressed by Chronic Lymphocytic Leukemia B Cells Show Limited Binding-Site Structure Variability

Anna Tramontano, Paolo Marcatili, Silvia Bruno, 2013, The Journal of Immunology.

Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

Anna Tramontano, Paolo Marcatili, Pier Paolo Olimpieri, 2014 .

IEDB-AR: immune epitope database—analysis resource in 2019

Morten Nielsen, Bjoern Peters, Alessandro Sette, 2019, Nucleic Acids Res..

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

Morten Nielsen, Ole Lund, Paolo Marcatili, 2017, PloS one.

Mutation Pattern of Paired Immunoglobulin Heavy and Light Variable Domains in Chronic Lymphocytic Leukemia B Cells

Anna Tramontano, Paolo Marcatili, Silvia Bruno, 2011, Molecular medicine.

Prediction of Antibody Epitopes.

Morten Nielsen, Paolo Marcatili, M. Nielsen, 2015, Methods in molecular biology.

NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data

Morten Nielsen, Vanessa Isabell Jurtz, Paolo Marcatili, 2017, bioRxiv.