Leveraging Non-negative Matrix Tri-Factorization and Knowledge-Based Embeddings for Drug Repurposing: an Application to Parkinson's Disease-Reference-Cited by-同舟云学术

Leveraging Non-negative Matrix Tri-Factorization and Knowledge-Based Embeddings for Drug Repurposing: an Application to Parkinson's Disease

Published:2023-11-09 Issue: Volume: Page:99-106
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Container-title:Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering
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Author:

Messa Letizia¹^ORCID,Testa Carolina¹^ORCID,Carelli Stephana²^ORCID,Rey Federica³^ORCID,Cereda Cristina²^ORCID,Raimondi Manuela Teresa⁴^ORCID,Ceri Stefano¹^ORCID,Pinoli Pietro¹^ORCID

Affiliation:

1. Department of Electronics,Information and Bioengineering (DEIB), Politecnico di Milano, Italy

2. Center of Functional Genomics and Rare Diseases, Buzzi Children's Hospital, Italy

3. Pediatric Clinical Research Center "Fondazione Romeo ed Enrica Invernizzi", DIBIC, University of Milan, Italy

4. Department of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Italy

Publisher

ACM

Link

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

Reference40 articles.

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2. Han Altae-Tran, Bharath Ramsundar, Aneesh S Pappu, and Vijay Pande. 2017. Low data drug discovery with one-shot learning. ACS central science 3, 4 (2017), 283–293.

3. Fingolimod as a Treatment in Neurologic Disorders Beyond Multiple Sclerosis

4. Non-negative Matrix Tri-Factorization for Data Integration and Network-based Drug Repositioning

5. Matrix Factorization-based Technique for Drug Repurposing Predictions

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