P. Marcatili

发表

Antibody Specific B-Cell Epitope Predictions: Leveraging Information From Antibody-Antigen Protein Complexes

M. Nielsen, Bjoern Peters, M. C. Jespersen, 2019, Front. Immunol..

Identification of the cognate peptide‐MHC target of T cell receptors using molecular modeling and force field scoring

M. Nielsen, P. Marcatili, Esteban Lanzarotti, 2018, Molecular immunology.

NetTCR: sequence-based prediction of TCR binding to peptide-MHC complexes using convolutional neural networks

M. Nielsen, Bjoern Peters, M. C. Jespersen, 2018, bioRxiv.

NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data

M. Nielsen, Bjoern Peters, P. Marcatili, 2017, The Journal of Immunology.

Structural repertoire of immunoglobulin λ light chains

A. Tramontano, D. Cirillo, P. Marcatili, 2011, Proteins.

Antibody informatics for drug discovery.

John P. Overington, K. Ikeda, M. Lefranc, 2014, Biochimica et biophysica acta.

Improved methods for predicting peptide binding affinity to MHC class II molecules

J. Greenbaum, M. Nielsen, Bjoern Peters, 2018, Immunology.

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

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

T cell receptor sequence clustering and antigen specificity

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

Modeled Structure of the Cell Envelope Proteinase of Lactococcus lactis

P. Marcatili, E. B. Hansen, 2020, Frontiers in Bioengineering and Biotechnology.

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

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

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.

Data mining patented antibody sequences

P. Marcatili, K. Krawczyk, Andrew Buchanan, 2020 .

Structural Characterization of Peptide Antibodies.

P. Marcatili, Anna Chailyan, 2015, Methods in molecular biology.

Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

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

Positive diversifying selection is a pervasive adaptive force throughout the Drosophila radiation.

P. Marcatili, B. Schlick-Steiner, F. M. Steiner, 2017, Molecular phylogenetics and evolution.

On the Mechanism of Chloroquine Resistance in Plasmodium falciparum

A. Tramontano, M. Chinappi, P. Marcatili, 2010, PloS one.

Identification of New Autoantigens by Protein Array Indicates a Role for IL4 Neutralization in Autoimmune Hepatitis*

F. Marabita, M. Marconi, P. Marcatili, 2012, Molecular & Cellular Proteomics.

Strategy to prevent epitope masking in CAR.CD19+ B-cell leukemia blasts

A. Órfão, P. Marcatili, F. Locatelli, 2021, Journal for ImmunoTherapy of Cancer.

Proteomic characterization of pilot scale hot-water extracts from the industrial carrageenan red seaweed Eucheuma denticulatum

M. Overgaard, P. Marcatili, S. Holdt, 2020, bioRxiv.

The ABCD database: a repository for chemically defined antibodies

A. Bairoch, P. Marcatili, E. Gasteiger, 2019, Nucleic Acids Res..

Additional file 3: Table S1. of A novel approach to probe host-pathogen interactions of bovine digital dermatitis, a model of a complex polymicrobial infection

M. Nielsen, P. Marcatili, C. Schafer-Nielsen, 2016 .

A novel approach to probe host-pathogen interactions of bovine digital dermatitis, a model of a complex polymicrobial infection

T. Sicheritz-Pontén, M. Nielsen, P. Marcatili, 2016, BMC Genomics.

T-cell Receptor Diversity Estimates for Repertoires (TCRDivER) uses sequence similarity to find signatures of immune response

Joseph Kaplinsky, T. Andresen, B. Chain, 2021, bioRxiv.

NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning

O. Winther, Henrik Nielsen, Bent Petersen, 2022, Nucleic Acids Res..

Terminal deoxynucleotidyl transferase-mediated formation of protein binding polynucleotides

P. Marcatili, Yi Sun, M. Mohammadniaei, 2021, Nucleic acids research.

Editorial: A Journey Through 50 Years of Structural Bioinformatics in Memoriam of Cyrus Chothia

A. Lesk, C. Deane, S. Teichmann, 2022, Frontiers in Molecular Biosciences.

Immunoglobulin G structure and rheumatoid factor epitopes

P. Højrup, P. Marcatili, Anna Chailyan, 2019, PloS one.

Identification of emulsifier potato peptides by bioinformatics: application to omega-3 delivery emulsions and release from potato industry side streams

M. Overgaard, P. Marcatili, M. Andersen, 2020, Scientific Reports.

T cell receptor sequence clustering and antigen speciﬁcity

Joseph Kaplinsky, P. Marcatili, Milena Vujović, 2020 .

BepiPred‐3.0: Improved B‐cell epitope prediction using protein language models

B. Peters, P. Marcatili, Morten Nielsen, 2022, bioRxiv.

Effects of natural selection and gene conversion on the evolution of human glycophorins coding for MNS blood polymorphisms in malaria-endemic African populations.

S. Tishkoff, P. Marcatili, Godfrey Lema, 2011, American journal of human genetics.

Antioxidant peptides derived from potato, seaweed, microbial and spinach proteins: Oxidative stability of 5% fish oil-in-water emulsions.

S. Hoffmann, M. Overgaard, P. Marcatili, 2022, Food chemistry.

A novel approach to probe host-pathogen interactions of bovine digital dermatitis, a model of a complex polymicrobial infection

T. Sicheritz-Pontén, M. Nielsen, P. Marcatili, 2016, BMC Genomics.

A database of immunoglobulins with integrated tools: DIGIT

Anna Tramontano, Anna Chailyan, Paolo Marcatili, 2011, Nucleic Acids Res..

Emulsifier peptides derived from seaweed, methanotrophic bacteria, and potato proteins identified by quantitative proteomics and bioinformatics.

M. Overgaard, P. Marcatili, C. Jacobsen, 2021, Food chemistry.

The structure, viscoelasticity and charge of potato peptides adsorbed at the oil-water interface determine the physicochemical stability of fish oil-in-water emulsions

S. Hoffmann, M. Overgaard, P. Marcatili, 2021 .

Emulsifying peptides from potato protein predicted by bioinformatics: Stabilization of fish oil-in-water emulsions

M. Overgaard, P. Marcatili, M. Andersen, 2020 .

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

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

AnOxPePred: using deep learning for the prediction of antioxidative properties of peptides

Ole Lund, Pedro J. García-Moreno, Egon Bech Hansen, 2020, Scientific Reports.

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia

Dimitrios Tzovaras, Ilias Kalamaras, Eleftheria Polychronidou, 2018, BMC Bioinformatics.

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

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

Prediction of Antibody Epitopes.

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

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

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

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.

DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks

Konstantinos D. Tsirigos, A. Krogh, Henrik Nielsen, 2022, bioRxiv.

Widespread amyloidogenicity potential of multiple myeloma patient-derived immunoglobulin light chains

Alexander K. Buell, S. Egelhaaf, P. Marcatili, 2023, BMC Biology.

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

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

LYRA, a webserver for lymphocyte receptor structural modeling

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

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.

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

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

Carboplatin-Oral Etoposide Personalised Dosing in Elderly Non-small Cell Lung Cancer Patients

P. Marcatili, S. Monfardini, G. Comella, 1998 .

Identification of emulsifier potato peptides by bioinformatics: application to omega-3 delivery emulsions and release from potato industry side streams

M. Overgaard, P. Marcatili, M. Andersen, 2020, Scientific Reports.

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.

NetSurfP‐2.0: Improved prediction of protein structural features by integrated deep learning

Ole Winther, Morten Nielsen, Michael Schantz Klausen, 2019, Proteins.

proABC-2: PRediction of AntiBody contacts v2 and its application to information-driven docking

F. Ambrosetti, T. H. Olsen, P. P. Olimpieri, 2020, bioRxiv.

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

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

The MoVIN server for the analysis of protein interaction networks

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

Human MHC-II with Shared Epitope Motifs Are Optimal Epstein-Barr Virus Glycoprotein 42 Ligands—Relation to Rheumatoid Arthritis

J. Izarzugaza, P. Marcatili, Anna Chailyan, 2018, International journal of molecular sciences.

TCRpMHCmodels: Structural modelling of TCR-pMHC class I complexes

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

T Cell Epitope Prediction and Its Application to Immunotherapy

P. Marcatili, S. Hadrup, Milena Vujović, 2021, Frontiers in Immunology.

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..

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.

Data mining patented antibody sequences

P. Marcatili, K. Krawczyk, Andrew Buchanan, 2020, bioRxiv.

PIGS: automatic prediction of antibody structures

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

Antibody modeling using the Prediction of ImmunoGlobulin Structure (PIGS) web server

Anna Tramontano, Pier Paolo Olimpieri, Anna Chailyan, 2014, Nature Protocols.

0 Chapter VI Network Cleansing : Reliable Interaction Networks

P. Marcatili, 2015 .

Selection and Modelling of a New Single-Domain Intrabody Against TDP-43

A. Pastore, P. Marcatili, A. Cattaneo, 2022, Frontiers in Molecular Biosciences.

FunClust: a web server for the identification of structural motifs in a set of non-homologous protein structures

Allegra Via, Gabriele Ausiello, Manuela Helmer-Citterich, 2008, BMC Bioinformatics.

3D Protein-Structure-Oriented Discovery of Clinical Relation Across Chronic Lymphocytic Leukemia Patients

Dimitrios Tzovaras, Panagiotis Moschonas, Eleftheria Polychronidou, 2017, IWBBIO.

Variance Analysis of LC-MS Experimental Factors and Their Impact on Machine Learning

P. Marcatili, V. Schwämmle, R. Röttger, 2023, bioRxiv.

Signatures of T cell immunity revealed using sequence similarity with TCRDivER algorithm

Joseph Kaplinsky, P. Marcatili, Milena Vujović, 2023, Communications Biology.

Carboplatin-oral etoposide personalized dosing in elderly non-small cell lung cancer patients. Gruppo Oncologico Cooperativo Sud-Italia.

P. Marcatili, S. Monfardini, G. Comella, 1998, European Journal of Cancer.

Recent advances in the production of emulsifying peptides with the aid of proteomics and bioinformatics

M. Overgaard, P. Marcatili, C. Jacobsen, 2023, Current Opinion in Food Science.

Benchmark datasets of immune receptor-epitope structural complexes

M. Nielsen, Bjoern Peters, A. Sette, 2019, BMC Bioinform..

Network cleansing: Reliable interaction networks

Anna Tramontano, Paolo Marcatili, A. Tramontano, 2009 .

Antioxidant peptides from alternative sources reduce lipid oxidation in 5% fish oil-in-water emulsions (pH 4) and fish oil-enriched mayonnaise.

M. Overgaard, P. Marcatili, C. Jacobsen, 2023, Food chemistry.

DiscoTope-3.0 - Improved B-cell epitope prediction using AlphaFold2 modeling and inverse folding latent representations

O. Winther, P. Marcatili, Morten Nielsen, 2023, bioRxiv.

Biofunctionality of Enzymatically Derived Peptides from Codfish (Gadus morhua) Frame: Bulk In Vitro Properties, Quantitative Proteomics, and Bioinformatic Prediction

M. Overgaard, P. Marcatili, C. Jacobsen, 2020, Marine drugs.

The ABCD database: a repository for chemically defined antibodies

A. Bairoch, P. Marcatili, E. Gasteiger, 2019, Nucleic Acids Res..

DiscoTope-3.0 - Improved B-cell epitope prediction using AlphaFold2 modeling and inverse folding latent representations

O. Winther, P. Marcatili, Morten Nielsen, 2023, bioRxiv.

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia

D. Tzovaras, K. Stamatopoulos, Xiao-Jie Yan, 2018, BMC Bioinformatics.

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

Dimitrios Tzovaras, Panagiotis Moschonas, Paolo Marcatili, 2016 .

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..

Immunoglobulin G structure and rheumatoid factor epitopes

P. Højrup, P. Marcatili, Anna Chailyan, 2019, PloS one.

Exploiting homology information in nontemplate based prediction of protein structures.

Anna Tramontano, Alfredo Iacoangeli, Paolo Marcatili, 2015, Journal of chemical theory and computation.

PIGS: automatic prediction of antibody structures

A. Tramontano, P. Marcatili, A. Rosi, 2008, Bioinform..

Comparative Structure Analysis of the Multi-Domain, Cell Envelope Proteases of Lactic Acid Bacteria

P. Marcatili, E. B. Hansen, M. H. Høie, 2023, Microorganisms.

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

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

Identification of the cognate peptide‐MHC target of T cell receptors using molecular modeling and force field scoring

M. Nielsen, P. Marcatili, Esteban Lanzarotti, 2018, Molecular immunology.

AnOxPePred: using deep learning for the prediction of antioxidative properties of peptides

M. Overgaard, P. Marcatili, C. Jacobsen, 2020, Scientific Reports.

Erratum: Antibody modeling using the Prediction of ImmunoGlobulin Structure (PIGS) web server

P. Marcatili, Anna Chailyan, P. Olimpieri, 2015, Nature Protocols.

Bioinformatically predicted emulsifying peptides and potato protein hydrolysate improves the oxidative stability of microencapsulated fish oil

M. Overgaard, P. Marcatili, F. Espejo-Carpio, 2022, bioRxiv.

Tabhu: tools for antibody humanization

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