Author

R. Egan

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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Cancer Biology· 1 Evolutionary Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Organism:C. elegans· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1

Frequent Co-Authors

A. Amzallag· 1 shared A. Friedman· 1 shared A. S. Saxena· 1 shared A. Sahu· 1 shared A. Wagner· 1 shared B. Foster· 1 shared B. Miao· 1 shared C. Benes· 1 shared

Activity by Year

2018-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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1 shared paperCancer Biology

A. Amzallag

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Genomic features predict bacterial life history strategies in soil, as identified by metagenomic stable isotope probing

S. E. Barnett, R. Egan, B. Foster, E. A. Eloe-Fadrosh, D. H. Buckley

The paper links genomic features of soil bacteria to their carbon acquisition and growth dynamics using metagenomic stable isotope probing, identifying genomic tradeoffs that align with life history theory predictions.

bioRxiv · Sep 9, 2022Microbiology

Head-to-Head Comparison of Three Methods of Quantifying Competitive Fitness in C. elegans

T. A. Crombie, S. Saber, A. S. Saxena, R. Egan, C. F. Baer

The paper compares three methods for quantifying competitive fitness in C. elegans, finding no significant differences in results but highlighting increased speed with automated tools.

bioRxiv · Jul 18, 2018Evolutionary Biology

Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

A. Sahu, J. Sang Lee, G. Zhang, Z. Wang, T. Tian, T. Moll, G. Kasumova, B. Miao, Z. Wei, N. U. Nair, O. Ponomarova, A. Friedman, A. Amzallag, P. Greninger, R. Egan, , E. Ruppin

The paper predicts synthetic rescue mediators of resistance to targeted and immunotherapy using tumor transcriptomics and survival data from 10,000 TCGA patients, validating predictions through experimental screens.

bioRxiv · Apr 8, 2018Cancer Biology