Author

S. S. Ericksen

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pharmacology & Toxicology· 2 Biochemistry· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 4 Approach:deep learning· 3 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Assay:proteomics· 1

Frequent Co-Authors

A. Gitter· 2 shared F. M. Hoffmann· 2 shared G. E. Ananiev· 2 shared J. D. Chan· 2 shared K. T. Ryan· 2 shared M. Zamanian· 2 shared S. A. Wildman· 2 shared A. F. Voter· 1 shared

Activity by Year

2018-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersPharmacology & Toxicology

A. Gitter

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Author profile →

4 papers

Recent·Most cited

Development of non-sedating antischistosomal benzodiazepines

M. Y. Mian, D. Sharmin, P. Mondal, J. B. Belayet, M. M. Hossain, P. McCusker, K. T. Ryan, A. Y. Fedorov, H. A. Green, S. S. Ericksen, M. Zamanian, V. V. N. Phani Babu Tiruveedhula, J. M. Cook, J. D. Chan

This paper develops non-sedating antischistosomal benzodiazepines by modifying meclonazepam's structure, identifying compounds effective in vivo with reduced sedation.

bioRxiv · Jan 26, 2024 · PreprintPharmacology & Toxicology

Multivariate chemogenomic screening prioritizes new macrofilaricidal leads

N. J. Wheeler, K. T. Ryan, K. J. Gallo, C. R. Henthorn, S. S. Ericksen, J. D. Chan, M. Zamanian

This study uses a multivariate screen to identify macrofilaricidal compounds, finding 17 compounds with strong effects on adult filariae and five with high potency against adults but low potency against microfilariae.

bioRxiv · Jul 25, 2022 · PreprintMicrobiology

Predicting kinase inhibitors using bioactivity matrix derived informer sets

H. Zhang, S. S. Ericksen, C.-p. Lee, G. E. Ananiev, N. Wlodarchak, J. C. Mitchell, A. Gitter, S. J. Wright, F. M. Hoffmann, S. A. Wildman, M. A. Newton

The paper develops an informer-based ranking method to predict kinase inhibitor activity using chemogenomic data, outperforming traditional chemical diversity-based approaches in both retrospective and prospective tests.

bioRxiv · Jan 28, 2019Pharmacology & Toxicology

Practical model selection for prospective virtual screening

S. Liu, M. Alnammi, S. S. Ericksen, A. F. Voter, G. E. Ananiev, J. L. Keck, F. M. Hoffmann, S. A. Wildman, A. Gitter

The paper evaluates virtual screening algorithms for two protein-protein interactions and finds random forest outperforms neural networks in prospective compound prioritization.

bioRxiv · Sep 15, 2018Biochemistry