Author

Elena L. Cáceres

University of California, San FranciscoORCID 0000-0002-2353-4350Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

Michael J. KeiseriD· 2 shared Bryan L. RothiD· 1 shared Leo GendeleviD· 1 shared Nicholas C. MewiD· 1 shared Seth D. AxeniD· 1 shared Xi‐Ping HuangiD· 1 shared

Activity by Year

2017-2020 · peak 1/yr

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6 top collaborators · 11 mutual co-author links

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2 shared papersBioinformatics

Michael J. KeiserORCID

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2 papers

Recent·Most cited

BioinformaticsJournal of Chemical Information and ModelingPeer-reviewedNov 27, 2020

Adding stochastic negative examples into machine learning improves molecular bioactivity prediction

Elena L. Cáceres, Nicholas C. Mew, Michael J. Keiser

This paper improves molecular bioactivity prediction by introducing stochastic negative examples during training, increasing drug-screening benchmark performance by 121.7%.

33 citations

machine learning (classical)drug response / drug discovery

𝕏 PostBluesky

BioinformaticsJournal of Medicinal ChemistryPeer-reviewedJul 21, 2017

A Simple Representation Of Three-Dimensional Molecular Structure

Seth D. Axen, Xi‐Ping Huang, Elena L. Cáceres…·Michael J. Keiser

This paper introduces a 3D molecular representation (E3FP) that improves drug-to-target prediction compared to 2D fingerprints, with experimental validation of novel binding predictions.

133 citationstop 3%

protein structurestatistical model

𝕏 PostBluesky