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Leveraging Non-negative Matrix Tri-Factorization and Knowle..:

, In: Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering,

Messa, Letizia ; Testa, Carolina ; Carelli, Stephana... - p. 99-106 , 2023

Link: https://dl.acm.org/doi/10.1145/3637732.3637783

RT 
T1 <cTitle>Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering</cTitle>: T1 <Title>Leveraging Non-negative Matrix Tri-Factorization and Knowledge-Based Embeddings for Drug Repurposing: an Application to Parkinson&#39;s Disease</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3637783&Exemplar=1&LAN=DE
				
A1 Messa, Letizia
A1 Testa, Carolina
A1 Carelli, Stephana
A1 Rey, Federica
A1 Cereda, Cristina
A1 Raimondi, Manuela Teresa
A1 Ceri, Stefano
A1 Pinoli, Pietro
PB ACM
YR 2023
K1 Drug Repurposing
K1 Embeddings
K1 Non-negative Matrix Tri-Factorization
K1 Parkinson's Disease
K1 Predictors
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Factorization methods
K1 Non-negative matrix factorization
K1 Learning latent representations
K1 Applied computing
K1 Life and medical sciences
K1 Computational biology
K1 Learning paradigms
K1 Supervised learning
K1 Supervised learning by classification
SP 99
OP 106
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3637732.3637783
DO https://dl.acm.org/doi/10.1145/3637732.3637783
SF ELIB - SuUB Bremen

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