Gabriele Orlando

Orcid: 0000-0002-5935-5258

According to our database1, Gabriele Orlando authored at least 16 papers between 2015 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Superradiant Quantum Phase Transition in Open Systems: System-Bath Interaction at the Critical Point.
Quantum, 2026

2025
Charting the structure-sequence landscape of light chain amyloids.
Bioinform., 2025

<i>In silico</i> identification of archaeal DNA-binding proteins.
Bioinform., 2025

FoldX force field revisited, an improved version.
Bioinform., 2025

2024
Integrating physics in deep learning algorithms: a force field as a PyTorch module.
Bioinform., 2024

2022
Editorial: Towards genome interpretation: Computational methods to model the genotype-phenotype relationship.
Frontiers Bioinform., 2022

2021
b2bTools: online predictions for protein biophysical features and their conservation.
Nucleic Acids Res., 2021

In silico prediction of in vitro protein liquid-liquid phase separation experiments outcomes with multi-head neural attention.
Bioinform., 2021

2020
Insight into the protein solubility driving forces with neural attention.
PLoS Comput. Biol., 2020

ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values.
Nucleic Acids Res., 2020

Accurate prediction of protein beta-aggregation with generalized statistical potentials.
Bioinform., 2020

2019
Computational identification of prion-like RNA-binding proteins that form liquid phase-separated condensates.
Bioinform., 2019

2018
Ultra-fast global homology detection with Discrete Cosine Transform and Dynamic Time Warping.
Bioinform., 2018

2017
DEOGEN2: prediction and interactive visualization of single amino acid variant deleteriousness in human proteins.
Nucleic Acids Res., 2017

SVM-dependent pairwise HMM: an application to protein pairwise alignments.
Bioinform., 2017

2015
Clustering-based model of cysteine co-evolution improves disulfide bond connectivity prediction and reduces homologous sequence requirements.
Bioinform., 2015


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