Article

High Dimensionality Reduction by Matrix Factorization for Systems Pharmacology

2021-05-30

Abstract excerpt

The extraction of predictive features from the complex high-dimensional multi-omic data is necessary for decoding and overcoming the therapeutic responses in systems pharmacology. Developing computational methods to reduce high-dimensional space of features in in vitro, in vivo and clinical data is essential to discover the evolution and mechanisms of the drug responses and drug resistance. In this paper, we have...

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Literature Corpus work: bd1c631b-89be-5cdd-8865-b8be21ae9aae
DOI: 10.1101/2021.05.30.446301

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