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Ran Elkon

Researcher at Tel Aviv University

Publications -  94
Citations -  6968

Ran Elkon is an academic researcher from Tel Aviv University. The author has contributed to research in topics: Gene & Regulation of gene expression. The author has an hindex of 37, co-authored 81 publications receiving 5905 citations. Previous affiliations of Ran Elkon include Weizmann Institute of Science & Netherlands Cancer Institute.

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Alternative cleavage and polyadenylation: extent, regulation and function

TL;DR: The current understanding of the polyadenylation process and the latest progress in the identification of APA events, mechanisms that regulate poly(A) site selection, and biological processes and diseases resulting from APA are reviewed.
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eRNAs are required for p53-dependent enhancer activity and gene transcription

TL;DR: This work ascribes transcription enhancement activity to p53 with the capacity to regulate multiple genes from a single genomic binding site and produces enhancer RNAs that are required for efficient transcriptional enhancement of interacting target genes and induction of a p53-dependent cell-cycle arrest.
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A Pumilio-induced RNA structure switch in p27-3′ UTR controls miR-221 and miR-222 accessibility

TL;DR: This work has uncovered a novel RBP-induced structural switch modulating microRNA-mediated gene expression regulation in quiescent cells, and induces a local change in RNA structure that favours association with miR-221 andMiR-222, efficient suppression of p27 expression, and rapid entry to the cell cycle.
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Functional genetic screens for enhancer elements in the human genome using CRISPR-Cas9

TL;DR: The approach expands the utility of CRISPR-Cas9 to elucidate the functions of the noncoding genome by identifying several functional enhancer elements and characterized the role of two of them in mediating p53 (TP53) and ERα (ESR1) gene regulation.
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EXPANDER – an integrative program suite for microarray data analysis

TL;DR: Expander 2.0 as mentioned in this paper is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response.