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PRODIGY: a web server for predicting the binding affinity of protein-protein complexes

Bioinformatics (Oxford, England), 2016-12, Vol.32 (23), p.3676-3678

2016

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Computational prediction of protein interfaces: A review of data driven methods

FEBS letters, 2015-11, Vol.589 (23), p.3516-3526

2015

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HomPPI: a class of sequence homology based protein-protein interface prediction methods

BMC bioinformatics, 2011-06, Vol.12 (1), p.244-244, Article 244

2011

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DeepRank: a deep learning framework for data mining 3D protein-protein interfaces

Nature communications, 2021-12, Vol.12 (1), p.7068-7068, Article 7068

2021

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RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins

PloS one, 2014-05, Vol.9 (5), p.e97725

2014

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iScore: a novel graph kernel-based function for scoring protein–protein docking models

Bioinformatics, 2020-01, Vol.36 (1), p.112-121

2020

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PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes

Frontiers in immunology, 2022-05, Vol.13, p.878762

2022

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PANDORA v2.0: Benchmarking peptide-MHC II models and software improvements

Frontiers in immunology, 2023, Vol.14, p.1285899-1285899

2023

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An overview of data‐driven HADDOCK strategies in CAPRI rounds 38‐45

Proteins, structure, function, and bioinformatics, 2020-08, Vol.88 (8), p.1029-1036

2020

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MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations

Biomolecules (Basel, Switzerland), 2023-01, Vol.13 (1), p.121

2023

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DeepRank-GNN: a graph neural network framework to learn patterns in protein–protein interfaces

Bioinformatics (Oxford, England), 2023-01, Vol.39 (1)

2023

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Entropy and Variability: A Second Opinion by Deep Learning

Biomolecules (Basel, Switzerland), 2022-11, Vol.12 (12), p.1740

2022

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Understanding structure-guided variant effect predictions using 3D convolutional neural networks

Frontiers in molecular biosciences, 2023-07, Vol.10, p.1204157

2023

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Large-scale prediction of binding affinity in protein-small ligand complexes: the PRODIGY-LIG web server

Bioinformatics (Oxford, England), 2019-05, Vol.35 (9), p.1585-1587

2019

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DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

Proteins, structure, function, and bioinformatics, 2014-02, Vol.82 (2), p.250-267

2014

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GradPose: a very fast and memory-efficient gradient descent-based tool for superimposing millions of protein structures from computational simulations

Bioinformatics (Oxford, England), 2023-08, Vol.39 (8)

2023

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iScore: An MPI supported software for ranking protein–protein docking models based on a random walk graph kernel and support vector machines

SoftwareX, 2020-01, Vol.11, p.100462, Article 100462

2020

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Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it?

Wiley interdisciplinary reviews. Computational molecular science, 2019-09, Vol.9 (5), p.e1410-n/a

2019

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iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations

Proteins, structure, function, and bioinformatics, 2019-02, Vol.87 (2), p.110-119

2019

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The PANDORA Software for Anchor-Restrained Peptide:MHC Modeling

Methods in molecular biology (Clifton, N.J.), 2023, Vol.2673, p.251

2023

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Performance of HADDOCK and a simple contact-based protein–ligand binding affinity predictor in the D3R Grand Challenge 2

Journal of computer-aided molecular design, 2018-01, Vol.32 (1), p.175-185

2018

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Protein–ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3

Journal of computer-aided molecular design, 2019-01, Vol.33 (1), p.83-91

2019

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Template-based protein-protein docking exploiting pairwise interfacial residue restraints

Briefings in bioinformatics, 2017-05, Vol.18 (3), p.458-466

2017

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Machine learning competition in immunology – Prediction of HLA class I binding peptides

Journal of immunological methods, 2011-11, Vol.374 (1), p.1-4

2011

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Protein-Protein Interface Predictions by Data-Driven Methods: A Review

FEBS letters, 2015-10, Vol.589 (23), p.3516-3526

2015

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PRODIGY: a web server for predicting the binding affinity of protein-protein complexes

Computational prediction of protein interfaces: A review of data driven methods

HomPPI: a class of sequence homology based protein-protein interface prediction methods

DeepRank: a deep learning framework for data mining 3D protein-protein interfaces

RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins

iScore: a novel graph kernel-based function for scoring protein–protein docking models

PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes

PANDORA v2.0: Benchmarking peptide-MHC II models and software improvements

An overview of data‐driven HADDOCK strategies in CAPRI rounds 38‐45

MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations

DeepRank-GNN: a graph neural network framework to learn patterns in protein–protein interfaces

Entropy and Variability: A Second Opinion by Deep Learning

Understanding structure-guided variant effect predictions using 3D convolutional neural networks

Large-scale prediction of binding affinity in protein-small ligand complexes: the PRODIGY-LIG web server

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

GradPose: a very fast and memory-efficient gradient descent-based tool for superimposing millions of protein structures from computational simulations

iScore: An MPI supported software for ranking protein–protein docking models based on a random walk graph kernel and support vector machines

Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it?

iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations

The PANDORA Software for Anchor-Restrained Peptide:MHC Modeling

Performance of HADDOCK and a simple contact-based protein–ligand binding affinity predictor in the D3R Grand Challenge 2

Protein–ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3

Template-based protein-protein docking exploiting pairwise interfacial residue restraints

Machine learning competition in immunology – Prediction of HLA class I binding peptides

Protein-Protein Interface Predictions by Data-Driven Methods: A Review

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