Author

A. Alshawabkeh

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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Microbiology· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:ecology & biodiversity· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Assay:proteomics· 1

Frequent Co-Authors

A. Z. Gu· 2 shared A. J. Pinto· 1 shared C. Velez Vega· 1 shared D. Kaeli· 1 shared I. Cotto· 1 shared I. Y. Padilla· 1 shared J. Dy· 1 shared J. F. Cordero· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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Curved chords = mutual co-authorship

2 shared papersMicrobiology

A. Z. Gu

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Spatial-temporal targeted and non-targeted surveys to assess microbiological composition of drinking water in Puerto Rico following Hurricane Maria.

M. C. Sevillano, S. Vosloo, I. Cotto, Z. Dai, T. Jiang, J. M. Santiago Santana, I. Y. Padilla, Z. Rosario-Pabon, C. Velez Vega, J. F. Cordero, A. Alshawabkeh, A. Z. Gu, A. J. Pinto

This study assessed drinking water microbiome changes in Puerto Rico after Hurricane Maria using targeted and non-targeted microbial analysis, finding no significant deterioration in biological quality.

bioRxiv · May 7, 2021Microbiology

Machine Learning-based Biomarkers Identification and Validation from Toxicogenomics - Bridging to Regulatory Relevant Phenotypic Endpoints

S. M. Rahman, J. Lan, D. Kaeli, J. Dy, A. Alshawabkeh, A. Z. Gu

The paper identifies and validates biomarkers using machine learning to predict in vivo phenotypic toxicity endpoints from in vitro toxicogenomic data.

bioRxiv · Dec 18, 2020Pharmacology & Toxicology