A recommendation system is proposed based on the construction of Knowledge Graphs, where physical interaction between proteins and associations between drugs and targets are taken into account. The system suggests new targets for a given drug depending on how proteins are linked each other in the graph. The framework adopted for the implementation of the proposed approach is Apache Spark, useful for loading, managing and manipulating data by means of appropriate Resilient Distributed Datasets (RDD). Moreover, the Alternating Least Square (ALS) machine learning algorithm, a Matrix Factorization algorithm for distributed and parallel computing, is applied. Preliminary obtained results seem to be promising.

Contini S., Rombo S.E. (2022). A Collaborative Filtering Approach for Drug Repurposing. In S. Chiusano, T. Cerquitelli, R. Wrembel, K. l Nørvåg, B. Catania, G. Vargas-Solar, et al. (a cura di), New Trends in Database and Information Systems (pp. 381-387). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-15743-1_35].

A Collaborative Filtering Approach for Drug Repurposing

Rombo S. E.
2022-01-01

Abstract

A recommendation system is proposed based on the construction of Knowledge Graphs, where physical interaction between proteins and associations between drugs and targets are taken into account. The system suggests new targets for a given drug depending on how proteins are linked each other in the graph. The framework adopted for the implementation of the proposed approach is Apache Spark, useful for loading, managing and manipulating data by means of appropriate Resilient Distributed Datasets (RDD). Moreover, the Alternating Least Square (ALS) machine learning algorithm, a Matrix Factorization algorithm for distributed and parallel computing, is applied. Preliminary obtained results seem to be promising.
2022
978-3-031-15742-4
978-3-031-15743-1
Contini S., Rombo S.E. (2022). A Collaborative Filtering Approach for Drug Repurposing. In S. Chiusano, T. Cerquitelli, R. Wrembel, K. l Nørvåg, B. Catania, G. Vargas-Solar, et al. (a cura di), New Trends in Database and Information Systems (pp. 381-387). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-15743-1_35].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/594953
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