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May 9, 2019
A deep learning approach to the structural analysis of proteins
Marco Giulini, Raffaello Potestio
The European Physical Journal. B
|
November 1, 2021
A journey through mapping space: characterising the statistical and metric properties of reduced representations of macromolecules
Roberto Menichetti, Marco Giulini, Raffaello Potestio
Physical Review. E
|
November 18, 2022
Making sense of complex systems through resolution, relevance, and mapping entropy
Roi Holtzman, Marco Giulini, Raffaello Potestio
Journal of Chemical Theory and Computation
|
October 27, 2020
An Information-Theory-Based Approach for Optimal Model Reduction of Biomolecules
Marco Giulini, Roberto Menichetti, M Scott Shell, et al.
Bioinformatics Advances
|
July 22, 2025
Improved prediction of antibody and their complexes with clustered generative modelling ensembles
Xiaotong Xu, Marco Giulini, Alexandre M J J Bonvin
Journal of Environmental Science and Health. Part C, Environmental Carcinogenesis & Ecotoxicology Reviews
|
January 11, 2019
Machine learning models for predicting endocrine disruption potential of environmental chemicals
Marco Chierici, Marco Giulini, Nicole Bussola, et al.
Journal of Chemical Information and Modeling
|
June 11, 2024
EXCOGITO, an Extensible Coarse-Graining Toolbox for the Investigation of Biomolecules by Means of Low-Resolution Representations
Marco Giulini, Raffaele Fiorentini, Luca Tubiana, et al.
Journal of Chemical Information and Modeling
|
October 3, 2024
Modeling Protein-Glycan Interactions with HADDOCK
Anna Ranaudo, Marco Giulini, Angela Pelissou Ayuso, et al.
Frontiers in Molecular Biosciences
|
May 17, 2021
A Deep Graph Network-Enhanced Sampling Approach to Efficiently Explore the Space of Reduced Representations of Proteins
Federico Errica, Marco Giulini, Davide Bacciu, et al.
Communications Biology
|
January 6, 2024
ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
Marco Giulini, Rodrigo V Honorato, Jesús L Rivera, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 17) with videos related to
Sort By:
Page
of 2
Interface Focus
|
May 9, 2019
A deep learning approach to the structural analysis of proteins
Marco Giulini, Raffaello Potestio
The European Physical Journal. B
|
November 1, 2021
A journey through mapping space: characterising the statistical and metric properties of reduced representations of macromolecules
Roberto Menichetti, Marco Giulini, Raffaello Potestio
Physical Review. E
|
November 18, 2022
Making sense of complex systems through resolution, relevance, and mapping entropy
Roi Holtzman, Marco Giulini, Raffaello Potestio
Journal of Chemical Theory and Computation
|
October 27, 2020
An Information-Theory-Based Approach for Optimal Model Reduction of Biomolecules
Marco Giulini, Roberto Menichetti, M Scott Shell, et al.
Bioinformatics Advances
|
July 22, 2025
Improved prediction of antibody and their complexes with clustered generative modelling ensembles
Xiaotong Xu, Marco Giulini, Alexandre M J J Bonvin
Journal of Environmental Science and Health. Part C, Environmental Carcinogenesis & Ecotoxicology Reviews
|
January 11, 2019
Machine learning models for predicting endocrine disruption potential of environmental chemicals
Marco Chierici, Marco Giulini, Nicole Bussola, et al.
Journal of Chemical Information and Modeling
|
June 11, 2024
EXCOGITO, an Extensible Coarse-Graining Toolbox for the Investigation of Biomolecules by Means of Low-Resolution Representations
Marco Giulini, Raffaele Fiorentini, Luca Tubiana, et al.
Journal of Chemical Information and Modeling
|
October 3, 2024
Modeling Protein-Glycan Interactions with HADDOCK
Anna Ranaudo, Marco Giulini, Angela Pelissou Ayuso, et al.
Frontiers in Molecular Biosciences
|
May 17, 2021
A Deep Graph Network-Enhanced Sampling Approach to Efficiently Explore the Space of Reduced Representations of Proteins
Federico Errica, Marco Giulini, Davide Bacciu, et al.
Communications Biology
|
January 6, 2024
ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
Marco Giulini, Rodrigo V Honorato, Jesús L Rivera, et al.
Page
of 2