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PANDORA v2.0: Benchmarking peptide-MHC II models and software improvements.
- Published in:
- Frontiers in Immunology, 2023, p. 1, doi. 10.3389/fimmu.2023.1285899
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- Article
GradPose: a very fast and memory-efficient gradient descent-based tool for superimposing millions of protein structures from computational simulations.
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- Bioinformatics, 2023, v. 39, n. 8, p. 1, doi. 10.1093/bioinformatics/btad444
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- Article
DeepRank-GNN: a graph neural network framework to learn patterns in protein–protein interfaces.
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- Bioinformatics, 2023, v. 39, n. 1, p. 1, doi. 10.1093/bioinformatics/btac759
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- Article
MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein–Protein Docking Conformations.
- Published in:
- Biomolecules (2218-273X), 2023, v. 13, n. 1, p. 121, doi. 10.3390/biom13010121
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- Article
Entropy and Variability: A Second Opinion by Deep Learning.
- Published in:
- Biomolecules (2218-273X), 2022, v. 12, n. 12, p. 1740, doi. 10.3390/biom12121740
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- Article
PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes.
- Published in:
- Frontiers in Immunology, 2022, v. 13, p. 1, doi. 10.3389/fimmu.2022.878762
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- Article
DeepRank: a deep learning framework for data mining 3D protein-protein interfaces.
- Published in:
- Nature Communications, 2021, v. 12, n. 1, p. 1, doi. 10.1038/s41467-021-27396-0
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- Article
An overview of data‐driven HADDOCK strategies in CAPRI rounds 38‐45.
- Published in:
- Proteins, 2020, v. 88, n. 8, p. 1029, doi. 10.1002/prot.25869
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- Article
iScore: a novel graph kernel-based function for scoring protein–protein docking models.
- Published in:
- Bioinformatics, 2020, v. 36, n. 1, p. 112, doi. 10.1093/bioinformatics/btz496
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- Article
Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it?
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- WIREs: Computational Molecular Science, 2019, v. 9, n. 5, p. N.PAG, doi. 10.1002/wcms.1410
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- Article
Large-scale prediction of binding affinity in protein–small ligand complexes: the PRODIGY-LIG web server.
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- Bioinformatics, 2019, v. 35, n. 9, p. 1585, doi. 10.1093/bioinformatics/bty816
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- Article
iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations.
- Published in:
- Proteins, 2019, v. 87, n. 2, p. 110, doi. 10.1002/prot.25630
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- Article
Protein-ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3.
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- Journal of Computer-Aided Molecular Design, 2019, v. 33, n. 1, p. 83, doi. 10.1007/s10822-018-0148-4
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- Article
Performance of HADDOCK and a simple contact-based protein-ligand binding affinity predictor in the D3R Grand Challenge 2.
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- Journal of Computer-Aided Molecular Design, 2018, v. 32, n. 1, p. 175, doi. 10.1007/s10822-017-0049-y
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- Article
Template-based protein-protein docking exploiting pairwise interfacial residue restraints.
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- Briefings in Bioinformatics, 2017, v. 18, n. 3, p. 458, doi. 10.1093/bib/bbw027
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- Article
PRODIGY: a web server for predicting the binding affinity of protein--protein complexes.
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- Bioinformatics, 2016, v. 32, n. 23, p. 3676, doi. 10.1093/bioinformatics/btw514
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- Article
Computational prediction of protein interfaces: A review of data driven methods.
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- FEBS Letters, 2015, v. 589, n. 23, p. 3516, doi. 10.1016/j.febslet.2015.10.003
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- Article
RNABindRPlus: A Predictor that Combines Machine Learning and Sequence Homology-Based Methods to Improve the Reliability of Predicted RNA-Binding Residues in Proteins.
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- PLoS ONE, 2014, v. 9, n. 5, p. 1, doi. 10.1371/journal.pone.0097725
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- Article
DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction.
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- Proteins, 2014, v. 82, n. 2, p. 250, doi. 10.1002/prot.24370
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- Article
HomPPI: a class of sequence homology based protein-protein interface prediction methods.
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- BMC Bioinformatics, 2011, v. 12, n. 1, p. 244, doi. 10.1186/1471-2105-12-244
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- Article