Emanuel Rosonina

2.0k total citations
27 papers, 1.5k citations indexed

About

Emanuel Rosonina is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Emanuel Rosonina has authored 27 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 4 papers in Oncology and 1 paper in Epidemiology. Recurrent topics in Emanuel Rosonina's work include RNA Research and Splicing (15 papers), Ubiquitin and proteasome pathways (10 papers) and Genomics and Chromatin Dynamics (9 papers). Emanuel Rosonina is often cited by papers focused on RNA Research and Splicing (15 papers), Ubiquitin and proteasome pathways (10 papers) and Genomics and Chromatin Dynamics (9 papers). Emanuel Rosonina collaborates with scholars based in Canada, United States and United Kingdom. Emanuel Rosonina's co-authors include Benjamin J. Blencowe, James L. Manley, Susan McCracken, Nova Fong, Stewart Shuman, David L. Bentley, David P. Siderovski, Krassimir Yankulov, Stephen Paul Foster and Andrew Hessel and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Emanuel Rosonina

27 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emanuel Rosonina Canada 19 1.4k 121 95 82 79 27 1.5k
G. Tony Moreno United States 9 1.3k 0.9× 144 1.2× 154 1.6× 67 0.8× 105 1.3× 9 1.5k
Benoı̂t Palancade France 23 1.3k 0.9× 118 1.0× 94 1.0× 74 0.9× 85 1.1× 42 1.4k
Olga V. Iarovaia Russia 19 1.1k 0.7× 128 1.1× 136 1.4× 67 0.8× 213 2.7× 63 1.3k
Nicholas J. Fuda United States 11 1.7k 1.2× 152 1.3× 133 1.4× 116 1.4× 130 1.6× 13 1.9k
Janis Werner United States 11 2.1k 1.5× 89 0.7× 169 1.8× 76 0.9× 160 2.0× 11 2.2k
Michelle T. Harreman United States 19 1.6k 1.1× 112 0.9× 135 1.4× 56 0.7× 100 1.3× 21 1.8k
Suisheng Zhang Germany 17 885 0.6× 96 0.8× 89 0.9× 83 1.0× 184 2.3× 25 1.1k
Rafael Cuesta United States 17 1.2k 0.8× 115 1.0× 221 2.3× 129 1.6× 66 0.8× 19 1.4k
Sylvain Egloff France 19 1.6k 1.1× 130 1.1× 91 1.0× 135 1.6× 94 1.2× 25 1.8k
Aline Marnef France 17 980 0.7× 106 0.9× 140 1.5× 75 0.9× 111 1.4× 21 1.1k

Countries citing papers authored by Emanuel Rosonina

Since Specialization
Citations

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

Fields of papers citing papers by Emanuel Rosonina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emanuel Rosonina. 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 Emanuel Rosonina. The network helps show where Emanuel Rosonina may publish in the future.

Co-authorship network of co-authors of Emanuel Rosonina

This figure shows the co-authorship network connecting the top 25 collaborators of Emanuel Rosonina. A scholar is included among the top collaborators of Emanuel Rosonina 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 Emanuel Rosonina. Emanuel Rosonina 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.
McNeil, J. Bryan, et al.. (2024). 1,10-phenanthroline inhibits sumoylation and reveals that yeast SUMO modifications are highly transient. EMBO Reports. 25(1). 68–81. 2 indexed citations
2.
McNeil, J. Bryan, et al.. (2023). Sumoylation is Largely Dispensable for Normal Growth but Facilitates Heat Tolerance in Yeast. Molecular and Cellular Biology. 43(1). 64–84. 5 indexed citations
3.
Burgener, Justin, et al.. (2021). Dynamic sumoylation of promoter-bound general transcription factors facilitates transcription by RNA polymerase II. PLoS Genetics. 17(9). e1009828–e1009828. 10 indexed citations
4.
Richard, P. & Emanuel Rosonina. (2021). Regulating autophagy: a novel role for SETX (Senataxin). Neural Regeneration Research. 16(10). 2008–2008. 4 indexed citations
5.
Rosonina, Emanuel, et al.. (2019). Sumoylation of DNA-bound transcription factor Sko1 prevents its association with nontarget promoters. PLoS Genetics. 15(2). e1007991–e1007991. 13 indexed citations
6.
Rosonina, Emanuel. (2019). A conserved role for transcription factor sumoylation in binding-site selection. Current Genetics. 65(6). 1307–1312. 17 indexed citations
7.
Ng, Chong Han, et al.. (2015). Sumoylation controls the timing of Tup1-mediated transcriptional deactivation. Nature Communications. 6(1). 6610–6610. 23 indexed citations
8.
Rosonina, Emanuel, et al.. (2012). Sumoylation of transcription factor Gcn4 facilitates its Srb10-mediated clearance from promoters in yeast. Genes & Development. 26(4). 350–355. 45 indexed citations
9.
Rosonina, Emanuel, et al.. (2010). SUMO functions in constitutive transcription and during activation of inducible genes in yeast. Genes & Development. 24(12). 1242–1252. 72 indexed citations
10.
Rosonina, Emanuel, Ian M. Willis, & James L. Manley. (2009). Sub1 Functions in Osmoregulation and in Transcription by both RNA Polymerases II and III. Molecular and Cellular Biology. 29(8). 2308–2321. 35 indexed citations
11.
Rosonina, Emanuel, Syuzo Kaneko, & James L. Manley. (2006). Terminating the transcript: breaking up is hard to do. Genes & Development. 20(9). 1050–1056. 95 indexed citations
12.
Rosonina, Emanuel, Joanna Y. Ip, John A. Calarco, et al.. (2005). Role for PSF in Mediating Transcriptional Activator-Dependent Stimulation of Pre-mRNA Processing In Vivo. Molecular and Cellular Biology. 25(15). 6734–6746. 102 indexed citations
13.
Rosonina, Emanuel & James L. Manley. (2005). From Transcription to mRNA: PAF Provides a New Path. Molecular Cell. 20(2). 167–168. 30 indexed citations
14.
Rosonina, Emanuel & Benjamin J. Blencowe. (2004). Analysis of the requirement for RNA polymerase II CTD heptapeptide repeats in pre-mRNA splicing and 3′-end cleavage. RNA. 10(4). 581–589. 50 indexed citations
15.
Rosonina, Emanuel, Malina A. Bakowski, Susan McCracken, & Benjamin J. Blencowe. (2003). Transcriptional Activators Control Splicing and 3′-End Cleavage Levels. Journal of Biological Chemistry. 278(44). 43034–43040. 55 indexed citations
16.
Rosonina, Emanuel & Benjamin J. Blencowe. (2002). Gene Expression: The Close Coupling of Transcription and Splicing. Current Biology. 12(9). R319–R321. 18 indexed citations
17.
Blencowe, Benjamin J., Göran Baurén, Adam G. Eldridge, et al.. (2000). The SRm160/300 splicing coactivator subunits. RNA. 6(1). 111–120. 89 indexed citations
18.
Blencowe, Benjamin J., et al.. (1999). SR-related proteins and the processing of messenger RNA precursors. Biochemistry and Cell Biology. 77(4). 277–291. 108 indexed citations
19.
McCracken, Susan, Emanuel Rosonina, Nova Fong, et al.. (1998). Role of RNA Polymerase II Carboxy-terminal Domain in Coordinating Transcription with RNA Processing. Cold Spring Harbor Symposia on Quantitative Biology. 63(0). 301–310. 37 indexed citations
20.
McCracken, Susan, Nova Fong, Emanuel Rosonina, et al.. (1997). 5′-Capping enzymes are targeted to pre-mRNA by binding to the phosphorylated carboxy-terminal domain of RNA polymerase II. Genes & Development. 11(24). 3306–3318. 437 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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