Author

Jin Jie Yao

GlaxoSmithKline (United States)ORCID 0000-0001-9186-459XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:matrix factorization· 1

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Mark R. Hurle· 1 shared Matthew R. NelsoniD· 1 shared Pankaj AgarwaliD· 1 shared

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2019-2019 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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1 shared paperBioinformatics

Mark R. Hurle

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1 paper

Recent·Most cited

BioinformaticsBMC BioinformaticsPeer-reviewedFeb 8, 2019

Predicting clinically promising therapeutic hypotheses using tensor factorization

Jin Jie Yao, Mark R. Hurle, Matthew R. Nelson, Pankaj Agarwal

The paper uses tensor factorization to predict successful therapeutic target-indication pairs by analyzing clinical trial data and comparing performance with other machine learning models.

10 citations

matrix factorizationbenchmarking

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