Daniele Raimondi
Orcid: 0000-0003-1157-1899
According to our database1,
Daniele Raimondi
authored at least 18 papers
between 2014 and 2024.
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Bibliography
2024
2023
How good Neural Networks interpretation methods really are? A quantitative benchmark.
CoRR, 2023
2022
Editorial: Towards genome interpretation: Computational methods to model the genotype-phenotype relationship.
Frontiers Bioinform., 2022
Fast and accurate inference of gene regulatory networks through robust precision matrix estimation.
Bioinform., 2022
2021
b2bTools: online predictions for protein biophysical features and their conservation.
Nucleic Acids Res., 2021
A novel method for data fusion over entity-relation graphs and its application to protein-protein interaction prediction.
Bioinform., 2021
In silico prediction of in vitro protein liquid-liquid phase separation experiments outcomes with multi-head neural attention.
Bioinform., 2021
2020
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
On-Board Unit Big Data: Short-term Traffic Forecasting in Urban Transportation Networks.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 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
Bioinform., 2017
2016
Multilevel biological characterization of exomic variants at the protein level significantly improves the identification of their deleterious effects.
Bioinform., 2016
2015
Clustering-based model of cysteine co-evolution improves disulfide bond connectivity prediction and reduces homologous sequence requirements.
Bioinform., 2015
2014
PLoS Comput. Biol., 2014