Inga Jarmoskaite

1.6k total citations · 1 hit paper
19 papers, 1.1k citations indexed

About

Inga Jarmoskaite is a scholar working on Molecular Biology, Social Psychology and Sociology and Political Science. According to data from OpenAlex, Inga Jarmoskaite has authored 19 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 1 paper in Social Psychology and 1 paper in Sociology and Political Science. Recurrent topics in Inga Jarmoskaite's work include RNA and protein synthesis mechanisms (15 papers), RNA Research and Splicing (14 papers) and RNA modifications and cancer (11 papers). Inga Jarmoskaite is often cited by papers focused on RNA and protein synthesis mechanisms (15 papers), RNA Research and Splicing (14 papers) and RNA modifications and cancer (11 papers). Inga Jarmoskaite collaborates with scholars based in United States, France and Germany. Inga Jarmoskaite's co-authors include Rick Russell, Daniel Herschlag, Pavanapuresan P. Vaidyanathan, Alan M. Lambowitz, Namita Bisaria, Söenke Seifert, Pilar Tijerina, William J. Greenleaf, Liang Guo and Kalli Kappel 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

Inga Jarmoskaite

18 papers receiving 1.1k citations

Hit Papers

How to measure and evalua... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Inga Jarmoskaite United States 13 882 73 60 46 42 19 1.1k
Fu‐Sen Liang United States 15 727 0.8× 94 1.3× 64 1.1× 76 1.7× 42 1.0× 37 933
Aaron A. Hoskins United States 23 1.3k 1.5× 94 1.3× 39 0.7× 52 1.1× 44 1.0× 57 1.5k
Roland Gamsjaeger Australia 19 1.2k 1.4× 145 2.0× 113 1.9× 55 1.2× 28 0.7× 46 1.4k
Gerard G. Lambert United States 11 795 0.9× 133 1.8× 67 1.1× 21 0.5× 47 1.1× 22 1.2k
Maarit Hellman Finland 17 476 0.5× 66 0.9× 79 1.3× 38 0.8× 28 0.7× 36 945
Karl Bihlmaier Germany 6 1.1k 1.2× 143 2.0× 39 0.7× 20 0.4× 59 1.4× 8 1.2k
Lutz Vogeley Ireland 14 690 0.8× 112 1.5× 57 0.9× 12 0.3× 49 1.2× 17 934
Joshua S. Grimley United States 13 865 1.0× 65 0.9× 53 0.9× 20 0.4× 22 0.5× 14 1.5k
Anthony P. Schuller United States 11 1.0k 1.2× 60 0.8× 56 0.9× 42 0.9× 50 1.2× 14 1.2k
Alexey К. Shaytan Russia 20 1.0k 1.2× 59 0.8× 120 2.0× 48 1.0× 53 1.3× 59 1.3k

Countries citing papers authored by Inga Jarmoskaite

Since Specialization
Citations

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

Fields of papers citing papers by Inga Jarmoskaite

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Inga Jarmoskaite

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

All Works

19 of 19 papers shown
1.
Vogel, Paul, Inga Jarmoskaite, Jonathan M. Geisinger, et al.. (2025). Stereo-random oligonucleotides enable efficient recruitment of ADAR in vitro and in vivo. Nature Communications. 16(1). 8849–8849.
2.
Jarmoskaite, Inga & Jin Billy Li. (2024). Multifaceted roles of RNA editing enzyme ADAR1 in innate immunity. RNA. 30(5). 500–511. 9 indexed citations
3.
Sadée, Christoph, Winston R. Becker, Inga Jarmoskaite, et al.. (2022). A comprehensive thermodynamic model for RNA binding by the Saccharomyces cerevisiae Pumilio protein PUF4. Nature Communications. 13(1). 4522–4522. 6 indexed citations
4.
Jarmoskaite, Inga, et al.. (2022). Measurement of ATP utilization in RNA unwinding and RNA chaperone activities by DEAD-box helicase proteins. Methods in enzymology on CD-ROM/Methods in enzymology. 673. 53–76. 1 indexed citations
5.
Liu, Xin, Tao Sun, Anna Shcherbina, et al.. (2021). Learning cis-regulatory principles of ADAR-based RNA editing from CRISPR-mediated mutagenesis. Nature Communications. 12(1). 2165–2165. 17 indexed citations
6.
Jarmoskaite, Inga, Pilar Tijerina, & Rick Russell. (2020). ATP utilization by a DEAD-box protein during refolding of a misfolded group I intron ribozyme. Journal of Biological Chemistry. 296. 100132–100132. 8 indexed citations
7.
Jarmoskaite, Inga, et al.. (2020). How to measure and evaluate binding affinities. eLife. 9. 322 indexed citations breakdown →
8.
Kappel, Kalli, Inga Jarmoskaite, Pavanapuresan P. Vaidyanathan, et al.. (2019). Blind tests of RNA–protein binding affinity prediction. Proceedings of the National Academy of Sciences. 116(17). 8336–8341. 18 indexed citations
9.
Jarmoskaite, Inga, Sarah K. Denny, Pavanapuresan P. Vaidyanathan, et al.. (2019). A Quantitative and Predictive Model for RNA Binding by Human Pumilio Proteins. Molecular Cell. 74(5). 966–981.e18. 41 indexed citations
10.
Becker, Winston R., Inga Jarmoskaite, Pavanapuresan P. Vaidyanathan, William J. Greenleaf, & Daniel Herschlag. (2019). Demonstration of protein cooperativity mediated by RNA structure using the human protein PUM2. RNA. 25(6). 702–712. 12 indexed citations
11.
Bisaria, Namita, Inga Jarmoskaite, & Daniel Herschlag. (2017). Lessons from Enzyme Kinetics Reveal Specificity Principles for RNA-Guided Nucleases in RNA Interference and CRISPR-Based Genome Editing. Cell Systems. 4(1). 21–29. 56 indexed citations
12.
Clark, Greg, Joshua Russell, Aimee K. Wessel, et al.. (2016). Science Educational Outreach Programs That Benefit Students and Scientists. PLoS Biology. 14(2). e1002368–e1002368. 83 indexed citations
13.
Kachroo, Aashiq H., et al.. (2015). Hexapeptides That Inhibit Processing of Branched DNA Structures Induce a Dynamic Ensemble of Holliday Junction Conformations. Journal of Biological Chemistry. 290(37). 22734–22746. 6 indexed citations
14.
Jarmoskaite, Inga, Hari Bhaskaran, Söenke Seifert, & Rick Russell. (2014). DEAD-box protein CYT-19 is activated by exposed helices in a group I intron RNA. Proceedings of the National Academy of Sciences. 111(29). E2928–36. 23 indexed citations
15.
Jarmoskaite, Inga & Rick Russell. (2014). RNA Helicase Proteins as Chaperones and Remodelers. Annual Review of Biochemistry. 83(1). 697–725. 200 indexed citations
16.
Mitchell, David, et al.. (2013). The Long-Range P3 Helix of the Tetrahymena Ribozyme Is Disrupted during Folding between the Native and Misfolded Conformations. Journal of Molecular Biology. 425(15). 2670–2686. 18 indexed citations
17.
Russell, Rick, Inga Jarmoskaite, & Alan M. Lambowitz. (2012). Toward a molecular understanding of RNA remodeling by DEAD-box proteins. RNA Biology. 10(1). 44–55. 70 indexed citations
18.
Mallam, Anna L., Inga Jarmoskaite, Pilar Tijerina, et al.. (2011). Solution structures of DEAD-box RNA chaperones reveal conformational changes and nucleic acid tethering by a basic tail. Proceedings of the National Academy of Sciences. 108(30). 12254–12259. 65 indexed citations
19.
Jarmoskaite, Inga & Rick Russell. (2010). DEAD‐box proteins as RNA helicases and chaperones. Wiley Interdisciplinary Reviews - RNA. 2(1). 135–152. 134 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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