Author

Justin Mower

Rice UniversityORCID 0000-0001-8832-4883Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:electronic health records· 1 Research Focus:perturbation response prediction· 1

Frequent Co-Authors

Devika SubramanianiD· 2 shared Trevor CoheniD· 2 shared Hannah A BurkhardtiD· 1 shared Jake Portanova· 1 shared Nathan B. MurrayiD· 1 shared

Activity by Year

2019-2019 · peak 2/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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2 shared papersBioinformatics

Devika SubramanianORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 2, 2019

aer2vec: Distributed Representations of Adverse Event Reporting System Data as a Means to Identify Drug/Side-Effect Associations

Jake Portanova, Nathan B. Murray, Justin Mower…·Trevor Cohen

This paper introduces aer2vec, a representation learning method for adverse event reporting system data to identify drug/side-effect associations, showing improved performance over traditional disproportionality metrics.

10 citations

electronic health recordsstatistical model

𝕏 PostBluesky

BioinformaticsbioRxivPreprintSep 30, 2019

Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications

Hannah A Burkhardt, Devika Subramanian, Justin Mower, Trevor Cohen

The paper applies ESP embeddings to predict drug-drug interactions, showing better performance, faster training, and simplicity compared to graph convolutional neural networks.

24 citations

statistical modeldeep learning

𝕏 PostBluesky