David E. Weinberg

3.4k total citations · 1 hit paper
18 papers, 2.3k citations indexed

About

David E. Weinberg is a scholar working on Molecular Biology, Plant Science and Immunology. According to data from OpenAlex, David E. Weinberg has authored 18 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 3 papers in Plant Science and 2 papers in Immunology. Recurrent topics in David E. Weinberg's work include RNA and protein synthesis mechanisms (15 papers), RNA modifications and cancer (10 papers) and RNA Research and Splicing (8 papers). David E. Weinberg is often cited by papers focused on RNA and protein synthesis mechanisms (15 papers), RNA modifications and cancer (10 papers) and RNA Research and Splicing (8 papers). David E. Weinberg collaborates with scholars based in United States and Ireland. David E. Weinberg's co-authors include David P. Bartel, Kotaro Nakanishi, Dinshaw J. Patel, Ines A. Drinnenberg, Gerald R. Fink, Brenton R. Graveley, Sophie Martin, Nathan Morris, Sara Olson and Kristian E. Baker and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

David E. Weinberg

18 papers receiving 2.3k citations

Hit Papers

Codon Optimality Is a Major Determinant of mRNA Stability 2015 2026 2018 2022 2015 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David E. Weinberg United States 13 2.0k 297 215 185 146 18 2.3k
Vicent Pelechano Sweden 29 3.1k 1.6× 297 1.0× 504 2.3× 168 0.9× 103 0.7× 76 3.5k
Leoš Shivaya Valášek Czechia 35 2.9k 1.5× 174 0.6× 98 0.5× 122 0.7× 63 0.4× 71 3.0k
Sander Granneman United Kingdom 39 4.4k 2.2× 152 0.5× 366 1.7× 359 1.9× 180 1.2× 69 4.7k
Howard M. Fried United States 21 2.3k 1.2× 304 1.0× 108 0.5× 248 1.3× 120 0.8× 31 2.6k
Lidia Vasiljeva United Kingdom 19 2.0k 1.0× 172 0.6× 182 0.8× 61 0.3× 117 0.8× 30 2.4k
Éric Batsché France 21 1.8k 0.9× 150 0.5× 265 1.2× 250 1.4× 366 2.5× 33 2.4k
Beate Schwer United States 44 5.1k 2.6× 439 1.5× 130 0.6× 296 1.6× 138 0.9× 133 5.6k
Josette Banroques France 21 2.1k 1.1× 229 0.8× 62 0.3× 223 1.2× 133 0.9× 40 2.4k
Stefan Washietl Austria 19 2.8k 1.4× 226 0.8× 896 4.2× 224 1.2× 83 0.6× 28 3.1k
Dmitry E. Andreev Russia 29 2.1k 1.1× 272 0.9× 112 0.5× 157 0.8× 104 0.7× 69 2.5k

Countries citing papers authored by David E. Weinberg

Since Specialization
Citations

This map shows the geographic impact of David E. Weinberg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David E. Weinberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David E. Weinberg more than expected).

Fields of papers citing papers by David E. Weinberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. Weinberg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David E. Weinberg. The network helps show where David E. Weinberg may publish in the future.

Co-authorship network of co-authors of David E. Weinberg

This figure shows the co-authorship network connecting the top 25 collaborators of David E. Weinberg. A scholar is included among the top collaborators of David E. Weinberg based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David E. Weinberg. David E. Weinberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Stojković, Vanja, David E. Weinberg, & Danica Galonić Fujimori. (2021). miCLIP-MaPseq Identifies Substrates of Radical SAM RNA-Methylating Enzyme Using Mechanistic Cross-Linking and Mismatch Profiling. Methods in molecular biology. 2298. 105–122. 2 indexed citations
2.
Getz, Matthew A., David E. Weinberg, Ines A. Drinnenberg, Gerald R. Fink, & David P. Bartel. (2020). Xrn1p acts at multiple steps in the budding-yeast RNAi pathway to enhance the efficiency of silencing. Nucleic Acids Research. 4 indexed citations
3.
Guenther, Ulf‐Peter, David E. Weinberg, Meghan Zubradt, et al.. (2018). The helicase Ded1p controls use of near-cognate translation initiation codons in 5′ UTRs. Nature. 559(7712). 130–134. 119 indexed citations
4.
Stojković, Vanja, et al.. (2018). miCLIP-MaPseq, a Substrate Identification Approach for Radical SAM RNA Methylating Enzymes. Journal of the American Chemical Society. 140(23). 7135–7143. 11 indexed citations
5.
Kostova, Kamena K., Kelsey Hickey, Beatriz A. Osuna, et al.. (2017). CAT-tailing as a fail-safe mechanism for efficient degradation of stalled nascent polypeptides. Science. 357(6349). 414–417. 112 indexed citations
6.
Thérizols, Gabriel, et al.. (2017). Accurate, Streamlined Analysis of mRNA Translation by Sucrose Gradient Fractionation. BIO-PROTOCOL. 7(19). 9 indexed citations
7.
Mugridge, Jeffrey S., et al.. (2017). Application of a Schizosaccharomyces pombe Edc1-fused Dcp1–Dcp2 decapping enzyme for transcription start site mapping. RNA. 24(2). 251–257. 8 indexed citations
8.
Osuna, Beatriz A., et al.. (2017). In vitro analysis of RQC activities provides insights into the mechanism and function of CAT tailing. eLife. 6. 54 indexed citations
9.
Odegaard, Justin I., Minwoo Lee, Yoshitaka Sogawa, et al.. (2016). Perinatal Licensing of Thermogenesis by IL-33 and ST2. Cell. 166(4). 841–854. 95 indexed citations
10.
Weinberg, David E., Premal Shah, Stephen W. Eichhorn, et al.. (2016). Improved Ribosome-Footprint and mRNA Measurements Provide Insights into Dynamics and Regulation of Yeast Translation. Cell Reports. 14(7). 1787–1799. 275 indexed citations
11.
Weinberg, David E., et al.. (2016). The fail-safe mechanism of post-transcriptional silencing of unspliced HAC1 mRNA. eLife. 5. 28 indexed citations
12.
Presnyak, Vladimir, Najwa Alhusaini, Sophie Martin, et al.. (2015). Codon Optimality Is a Major Determinant of mRNA Stability. Cell. 160(6). 1111–1124. 697 indexed citations breakdown →
13.
Nakanishi, Kotaro, David E. Weinberg, David P. Bartel, & Dinshaw J. Patel. (2012). Structure of yeast Argonaute with guide RNA. Nature. 486(7403). 368–374. 277 indexed citations
14.
Sim, Soyeong, Jie Yao, David E. Weinberg, et al.. (2011). The zipcode-binding protein ZBP1 influences the subcellular location of the Ro 60-kDa autoantigen and the noncoding Y3 RNA. RNA. 18(1). 100–110. 35 indexed citations
15.
Weinberg, David E., Kotaro Nakanishi, Dinshaw J. Patel, & David P. Bartel. (2011). The Inside-Out Mechanism of Dicers from Budding Yeasts. Cell. 146(2). 262–276. 54 indexed citations
16.
Bernstein, Douglas A., Valmik K. Vyas, David E. Weinberg, et al.. (2011). Candida albicans Dicer (CaDcr1) is required for efficient ribosomal and spliceosomal RNA maturation. Proceedings of the National Academy of Sciences. 109(2). 523–528. 44 indexed citations
17.
Drinnenberg, Ines A., David E. Weinberg, Kathleen T. Xie, et al.. (2009). RNAi in Budding Yeast. Science. 326(5952). 544–550. 399 indexed citations
18.
Sim, Soyeong, David E. Weinberg, Gabriele Fuchs, et al.. (2008). The Subcellular Distribution of an RNA Quality Control Protein, the Ro Autoantigen, Is Regulated by Noncoding Y RNA Binding. Molecular Biology of the Cell. 20(5). 1555–1564. 68 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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