Caroline E. Shamu

6.5k total citations · 3 hit papers
22 papers, 4.4k citations indexed

About

Caroline E. Shamu is a scholar working on Molecular Biology, Cell Biology and Epidemiology. According to data from OpenAlex, Caroline E. Shamu has authored 22 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Cell Biology and 3 papers in Epidemiology. Recurrent topics in Caroline E. Shamu's work include Endoplasmic Reticulum Stress and Disease (6 papers), RNA and protein synthesis mechanisms (5 papers) and Molecular Biology Techniques and Applications (4 papers). Caroline E. Shamu is often cited by papers focused on Endoplasmic Reticulum Stress and Disease (6 papers), RNA and protein synthesis mechanisms (5 papers) and Molecular Biology Techniques and Applications (4 papers). Caroline E. Shamu collaborates with scholars based in United States, United Kingdom and Hong Kong. Caroline E. Shamu's co-authors include Peter Walter, Jeffery S. Cox, Peter Walter, Michael M. Shen, Betsy Hirsch, David Zarkower, Jonathan Hodgkin, Christopher S. Raymond, Hidde L. Ploegh and Tom A. Rapoport and has published in prestigious journals such as Nature, Cell and Nature Reviews Molecular Cell Biology.

In The Last Decade

Caroline E. Shamu

22 papers receiving 4.4k citations

Hit Papers

Oligomerization and phosp... 1993 2026 2004 2015 1996 1993 1998 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Caroline E. Shamu 2.8k 1.8k 862 792 436 22 4.4k
Nobumoto Watanabe 3.9k 1.4× 1.9k 1.1× 253 0.3× 450 0.6× 382 0.9× 128 5.7k
Sally Kornbluth 6.6k 2.4× 2.1k 1.1× 784 0.9× 520 0.7× 807 1.9× 109 8.2k
Raúl Méndez 4.9k 1.8× 841 0.5× 519 0.6× 455 0.6× 358 0.8× 71 6.1k
E Erikson 5.6k 2.0× 1.8k 1.0× 302 0.4× 1.4k 1.7× 507 1.2× 70 7.1k
Noriko Oshiro 5.3k 1.9× 1.6k 0.9× 1.9k 2.2× 252 0.3× 635 1.5× 34 7.3k
Lars Ellgaard 4.7k 1.7× 4.0k 2.2× 1.2k 1.4× 521 0.7× 1.2k 2.8× 62 7.5k
Robert J. Deschenes 4.9k 1.8× 1.8k 1.0× 444 0.5× 361 0.5× 322 0.7× 68 6.3k
Yair Argon 3.1k 1.1× 2.4k 1.3× 684 0.8× 340 0.4× 1.3k 3.1× 86 5.2k
Tohru Kataoka 6.7k 2.4× 1.7k 1.0× 249 0.3× 543 0.7× 763 1.8× 122 8.2k
Rein Aasland 4.2k 1.5× 902 0.5× 432 0.5× 684 0.9× 301 0.7× 58 5.4k

Countries citing papers authored by Caroline E. Shamu

Since Specialization
Citations

This map shows the geographic impact of Caroline E. Shamu'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 Caroline E. Shamu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Caroline E. Shamu more than expected).

Fields of papers citing papers by Caroline E. Shamu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Caroline E. Shamu. 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 Caroline E. Shamu. The network helps show where Caroline E. Shamu may publish in the future.

Co-authorship network of co-authors of Caroline E. Shamu

This figure shows the co-authorship network connecting the top 25 collaborators of Caroline E. Shamu. A scholar is included among the top collaborators of Caroline E. Shamu 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 Caroline E. Shamu. Caroline E. Shamu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mohr, Stephanie E., Jennifer A. Smith, Caroline E. Shamu, Ralph A. Neumüller, & Norbert Perrimon. (2014). RNAi screening comes of age: improved techniques and complementary approaches. Nature Reviews Molecular Cell Biology. 15(9). 591–600. 247 indexed citations
3.
Yilmazel, Bahar, Yanhui Hu, Frederic Sigoillot, et al.. (2014). Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis. BMC Bioinformatics. 15(1). 192–192. 32 indexed citations
4.
Xie, Tiao, Stefan Florian, Nathan J. Moerke, et al.. (2013). Differential Determinants of Cancer Cell Insensitivity to Antimitotic Drugs Discriminated by a One-Step Cell Imaging Assay. SLAS DISCOVERY. 18(9). 1062–1071. 4 indexed citations
5.
Shamu, Caroline E., Stefan Wiemann, & Michael Boutros. (2012). On target: A public repository for large-scale RNAi experiments. Nature Cell Biology. 14(2). 115–115. 7 indexed citations
6.
Harris, Eric S. J., Andrew Tolopko, Shugeng Cao, et al.. (2011). Traditional Medicine Collection Tracking System (TM-CTS): A database for ethnobotanically driven drug-discovery programs. Journal of Ethnopharmacology. 135(2). 590–593. 10 indexed citations
7.
Hoffman, Gregory R., et al.. (2010). A High-Throughput, Cell-Based Screening Method for siRNA and Small Molecule Inhibitors of mTORC1 Signaling Using the In Cell Western Technique. Assay and Drug Development Technologies. 8(2). 186–199. 30 indexed citations
8.
Tolopko, Andrew, John P. Sullivan, David M. Wrobel, et al.. (2010). Screensaver: an open source lab information management system (LIMS) for high throughput screening facilities. BMC Bioinformatics. 11(1). 260–260. 23 indexed citations
9.
10.
Birmingham, Amanda, Laura M. Selfors, Thorsten Forster, et al.. (2009). Statistical methods for analysis of high-throughput RNA interference screens. Nature Methods. 6(8). 569–575. 439 indexed citations
11.
Xie, Tiao, et al.. (2009). An Intermittent Live Cell Imaging Screen for siRNA Enhancers and Suppressors of a Kinesin-5 Inhibitor. PLoS ONE. 4(10). e7339–e7339. 21 indexed citations
12.
Inglese, James, Caroline E. Shamu, & R. Kiplin Guy. (2007). Reporting data from high-throughput screening of small-molecule libraries. Nature Chemical Biology. 3(8). 438–441. 79 indexed citations
13.
Shamu, Caroline E., Dennis Flierman, Hidde L. Ploegh, Tom A. Rapoport, & Vincent Chau. (2001). Polyubiquitination Is Required for US11-dependent Movement of MHC Class I Heavy Chain from Endoplasmic Reticulum into Cytosol. Molecular Biology of the Cell. 12(8). 2546–2555. 111 indexed citations
14.
Casagrande, Rocco, Patrick Stern, Maximilian Diehn, et al.. (2000). Degradation of Proteins from the ER of S. cerevisiae Requires an Intact Unfolded Protein Response Pathway. Molecular Cell. 5(4). 729–735. 154 indexed citations
15.
Shamu, Caroline E.. (1998). Splicing: HACking into the unfolded-protein response. Current Biology. 8(4). R121–R123. 26 indexed citations
16.
Raymond, Christopher S., Caroline E. Shamu, Michael M. Shen, et al.. (1998). Evidence for evolutionary conservation of sex-determining genes. Nature. 391(6668). 691–695. 619 indexed citations breakdown →
17.
Shamu, Caroline E.. (1997). Signal transduction: Splicing together the unfolded-protein response. Current Biology. 7(2). R67–R70. 31 indexed citations
18.
Shamu, Caroline E., Jeffery S. Cox, & Peter Walter. (1994). The unfolded-protein-response pathway in yeast. Trends in Cell Biology. 4(2). 56–60. 130 indexed citations
19.
Cox, Jeffery S., Caroline E. Shamu, & Peter Walter. (1993). Transcriptional induction of genes encoding endoplasmic reticulum resident proteins requires a transmembrane protein kinase. Cell. 73(6). 1197–1206. 989 indexed citations breakdown →
20.
Miller, David M., Michael M. Shen, Caroline E. Shamu, et al.. (1992). C. elegans unc-4 gene encodes a homeodomain protein that determines the pattern of synaptic input to specific motor neurons. Nature. 355(6363). 841–845. 156 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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