A Non-Negative Matrix Tri-Factorization based Method for Predicting Antitumor Drug Sensitivity

Pido, S.; Testa, C.; Pinoli, P.

doi:10.1101/2021.12.03.471100

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bioRxiv · 10.1101/2021.12.03.471100

A Non-Negative Matrix Tri-Factorization based Method for Predicting Antitumor Drug Sensitivity

Pido, S.·Testa, C.·Pinoli, P.

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Abstract

Large annotated cell line collections have been proven to enable the prediction of drug response in the preclinical setting. We present an enhancement of Non-Negative Matrix Tri-Factorization method, which allows the integration of different data types for the prediction of missing associations. To test our method we retrieved a dataset from CCLE, containing the connections among cell lines and drugs by means of their IC50 values. We performed two different kind of experiments: a) prediction of missing values in the matrix, b) prediction of the complete drug profile of a new cell line, demonstrating the validity of the method in both scenarios.

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Pido, S., Testa, C., Pinoli, P.. 2021-12-06. A Non-Negative Matrix Tri-Factorization based Method for Predicting Antitumor Drug Sensitivity. https://doi.org/10.1101/2021.12.03.471100

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