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Andrea Mastropietro

Showing results (1-10 of 9) with videos related to

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STAR Protocols|April 12, 2024
Protocol to explain support vector machine predictions via exact Shapley value computationAndrea Mastropietro, Jürgen Bajorath
STAR Protocols|January 3, 2023
Protocol to explain graph neural network predictions using an edge-centric Shapley value-based approachAndrea Mastropietro, Giuseppe Pasculli, Jürgen Bajorath
Scientific Reports|November 10, 2023
Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernelAndrea Mastropietro, Christian Feldmann, Jürgen Bajorath
Bioinformatics (Oxford, England)|August 2, 2023
XGDAG: explainable gene-disease associations via graph neural networksAndrea Mastropietro, Gianluca De Carlo, Aris Anagnostopoulos
Scientific Reports|June 29, 2026
Explainable artificial intelligence reveals divergent learning in pharmacophore-based hierarchical pooling graph neural networksMaria Julia Teja Urrutia, Andrea Mastropietro, Jürgen Bajorath
NAR Genomics and Bioinformatics|February 2, 2026
A novel explainable deep-learning approach for network analysis of epistatic interactionsAndrea Mastropietro, Georgios Markopoulos, Evangelos Evangelou, et al.
Bioinformatics (Oxford, England)|February 2, 2023
NIAPU: network-informed adaptive positive-unlabeled learning for disease gene identificationPaola Stolfi, Andrea Mastropietro, Giuseppe Pasculli, et al.
Iscience|September 22, 2022
EdgeSHAPer: Bond-centric Shapley value-based explanation method for graph neural networksAndrea Mastropietro, Giuseppe Pasculli, Christian Feldmann, et al.
Biomedicines|July 27, 2022
Network Proximity-Based Drug Repurposing Strategy for Early and Late Stages of Primary Biliary CholangitisEndrit Shahini, Giuseppe Pasculli, Andrea Mastropietro, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
STAR Protocols|April 12, 2024
Protocol to explain support vector machine predictions via exact Shapley value computationAndrea Mastropietro, Jürgen Bajorath
STAR Protocols|January 3, 2023
Protocol to explain graph neural network predictions using an edge-centric Shapley value-based approachAndrea Mastropietro, Giuseppe Pasculli, Jürgen Bajorath
Scientific Reports|November 10, 2023
Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernelAndrea Mastropietro, Christian Feldmann, Jürgen Bajorath
Bioinformatics (Oxford, England)|August 2, 2023
XGDAG: explainable gene-disease associations via graph neural networksAndrea Mastropietro, Gianluca De Carlo, Aris Anagnostopoulos
Scientific Reports|June 29, 2026
Explainable artificial intelligence reveals divergent learning in pharmacophore-based hierarchical pooling graph neural networksMaria Julia Teja Urrutia, Andrea Mastropietro, Jürgen Bajorath
NAR Genomics and Bioinformatics|February 2, 2026
A novel explainable deep-learning approach for network analysis of epistatic interactionsAndrea Mastropietro, Georgios Markopoulos, Evangelos Evangelou, et al.
Bioinformatics (Oxford, England)|February 2, 2023
NIAPU: network-informed adaptive positive-unlabeled learning for disease gene identificationPaola Stolfi, Andrea Mastropietro, Giuseppe Pasculli, et al.
Iscience|September 22, 2022
EdgeSHAPer: Bond-centric Shapley value-based explanation method for graph neural networksAndrea Mastropietro, Giuseppe Pasculli, Christian Feldmann, et al.
Biomedicines|July 27, 2022
Network Proximity-Based Drug Repurposing Strategy for Early and Late Stages of Primary Biliary CholangitisEndrit Shahini, Giuseppe Pasculli, Andrea Mastropietro, et al.
Pageof 1