Author

Roni Rasnic

Eleven Therapeutics (UK) Ltd. (United Kingdom)ORCID 0000-0002-1200-6325Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:experimental assay· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Organism:human· 1 Organism:mouse· 1 Approach:statistical model· 1 Organism:virus· 1

Frequent Co-Authors

Ahmet Can BerkyurekiD· 2 shared Ilaria Falciatori· 2 shared Omer WeissbrodiD· 2 shared Yaniv ErlichiD· 2 shared Adi Naamti· 1 shared Christopher Cole HoneycuttiD· 1 shared Daniel C. DouekiD· 1 shared Dario BressaniD· 1 shared

Activity by Year

2017-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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2 shared papersGenomics

Ahmet Can BerkyurekORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Genome wide screen of RNAi molecules against SARS-CoV-2 creates a broadly potent prophylaxis

Ohad Yogev, Omer Weissbrod, Giorgia Battistoni, Dario Bressan, Adi Naamti, Ilaria Falciatori, Ahmet Can Berkyurek, Roni Rasnic, Myra D.T. Hosmillo, Shaul Ilan, Iris Grossman, Lauren McCormick, Christopher Cole Honeycutt, Timothy S. Johnston, Matthew Gagné, , Yaniv Erlich

The paper identifies potent siRNAs against SARS-CoV-2 through RNAi screening, validates their efficacy against variants, and demonstrates their prophylactic potential in a hamster model.

bioRxiv · Apr 12, 2022 · PreprintGenomics

A scalable pipeline for SARS-CoV-2 replicon construction based on de-novo synthesis

Ahmet Can Berkyurek, Elian Lee, Omer Weissbrod, Roni Rasnic, Ilaria Falciatori, Siyuan Chen, Yaniv Erlich

The paper describes a scalable pipeline for constructing SARS-CoV-2 replicons using de-novo synthesis, demonstrating their safety and utility for drug testing.

bioRxiv · Feb 5, 2022 · PreprintSynthetic Biology

Lowest expressing microRNAs capture indispensable information - identifying cancer types

Roni Rasnic, Nathan Linial, Michal Linial B

This study identifies cancer types using lowly expressed microRNAs from TCGA data, achieving 91% recall after data discretization.

Nucleic Acids Research · Mar 31, 2017Peer-reviewedBioinformatics