Giedrius Vilkaitis

1.1k total citations
29 papers, 883 citations indexed

About

Giedrius Vilkaitis is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Giedrius Vilkaitis has authored 29 papers receiving a total of 883 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 6 papers in Genetics and 4 papers in Plant Science. Recurrent topics in Giedrius Vilkaitis's work include RNA modifications and cancer (15 papers), Epigenetics and DNA Methylation (14 papers) and Cancer-related gene regulation (5 papers). Giedrius Vilkaitis is often cited by papers focused on RNA modifications and cancer (15 papers), Epigenetics and DNA Methylation (14 papers) and Cancer-related gene regulation (5 papers). Giedrius Vilkaitis collaborates with scholars based in Lithuania, Czechia and United States. Giedrius Vilkaitis's co-authors include Saulius Klimašauskas, Isao Suetake, Shoji Tajima, Elmar G. Weinhold, Saulius Serva, Viktoras Masevičius, Česlovas Venclovas, Arūnas Lagunavičius, Virginijus Šikšnys and Arvydas Lubys and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Giedrius Vilkaitis

28 papers receiving 871 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Giedrius Vilkaitis Lithuania 18 776 149 118 84 58 29 883
Angela Borden United States 13 877 1.1× 229 1.5× 90 0.8× 175 2.1× 40 0.7× 14 935
Marc Bichara France 14 751 1.0× 232 1.6× 118 1.0× 181 2.2× 49 0.8× 22 852
Roger Kahn United States 11 603 0.8× 226 1.5× 39 0.3× 54 0.6× 78 1.3× 14 727
Viswanath Bandaru United States 13 796 1.0× 122 0.8× 49 0.4× 92 1.1× 29 0.5× 15 871
Cecilia Svensson Germany 10 418 0.5× 166 1.1× 28 0.2× 47 0.6× 64 1.1× 11 502
Constance L. Fisher United States 8 433 0.6× 150 1.0× 60 0.5× 29 0.3× 44 0.8× 12 598
Lawrence A. Loeb United States 10 537 0.7× 117 0.8× 71 0.6× 133 1.6× 37 0.6× 10 724
Danielle L. Watt United States 10 1.0k 1.3× 167 1.1× 71 0.6× 152 1.8× 27 0.5× 11 1.2k
J. William Efcavitch United States 13 494 0.6× 102 0.7× 42 0.4× 41 0.5× 47 0.8× 16 622
Ekaterina Kashkina United States 10 534 0.7× 126 0.8× 55 0.5× 44 0.5× 49 0.8× 11 576

Countries citing papers authored by Giedrius Vilkaitis

Since Specialization
Citations

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

Fields of papers citing papers by Giedrius Vilkaitis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giedrius Vilkaitis

This figure shows the co-authorship network connecting the top 25 collaborators of Giedrius Vilkaitis. A scholar is included among the top collaborators of Giedrius Vilkaitis 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 Giedrius Vilkaitis. Giedrius Vilkaitis 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.
Krasauskas, Renatas, Kotryna Kvederavičiūtė, Algirdas Kaupinis, et al.. (2023). Interplay between bacterial 5′-NAD-RNA decapping hydrolase NudC and DEAD-box RNA helicase CsdA in stress responses. mSystems. 8(5). e0071823–e0071823.
2.
Stankevičius, Vaidotas, et al.. (2022). Selective chemical tracking of Dnmt1 catalytic activity in live cells. Molecular Cell. 82(5). 1053–1065.e8. 13 indexed citations
3.
Masevičius, Viktoras, et al.. (2018). Animal Hen1 2′-O-methyltransferases as tools for 3′-terminal functionalization and labelling of single-stranded RNAs. Nucleic Acids Research. 46(17). e104–e104. 19 indexed citations
4.
Vilkaitis, Giedrius, et al.. (2018). Repurposing enzymatic transferase reactions for targeted labeling and analysis of DNA and RNA. Current Opinion in Biotechnology. 55. 114–123. 24 indexed citations
5.
Masevičius, Viktoras, et al.. (2017). Oligonucleotide‐Addressed Covalent 3′‐Terminal Derivatization of Small RNA Strands for Enrichment and Visualization. Angewandte Chemie International Edition. 56(23). 6507–6510. 14 indexed citations
6.
7.
Finke, Andreas, et al.. (2015). Functional mapping of the plant small RNA methyltransferase: HEN1 physically interacts with HYL1 and DICER-LIKE 1 proteins. Nucleic Acids Research. 43(5). 2802–2812. 67 indexed citations
8.
Klimašauskas, Saulius, et al.. (2013). Mechanistic insights into small RNA recognition and modification by the HEN1 methyltransferase. Biochemical Journal. 453(2). 281–290. 12 indexed citations
9.
10.
Gerasimaitė, Rūta, Giedrius Vilkaitis, & Saulius Klimašauskas. (2009). A directed evolution design of a GCG-specific DNA hemimethylase. Nucleic Acids Research. 37(21). 7332–7341. 19 indexed citations
11.
Yang, Zhiyong, Giedrius Vilkaitis, Bin Yu, Saulius Klimašauskas, & Xuemei Chen. (2007). Approaches for Studying MicroRNA and Small Interfering RNA Methylation In Vitro and In Vivo. Methods in enzymology on CD-ROM/Methods in enzymology. 427. 139–154. 29 indexed citations
12.
Serva, Saulius, et al.. (2004). HhaI DNA Methyltransferase Uses the Protruding Gln237 for Active Flipping of Its Target Cytosine. Structure. 12(6). 1047–1055. 30 indexed citations
13.
Vilkaitis, Giedrius, Isao Suetake, Saulius Klimašauskas, & Shoji Tajima. (2004). Processive Methylation of Hemimethylated CpG Sites by Mouse Dnmt1 DNA Methyltransferase. Journal of Biological Chemistry. 280(1). 64–72. 153 indexed citations
14.
Daujotyte, D., Giedrius Vilkaitis, Laura Manelytė, et al.. (2003). Solubility engineering of the HhaI methyltransferase. Protein Engineering Design and Selection. 16(4). 295–301. 19 indexed citations
15.
Vilkaitis, Giedrius. (2002). Circular permutation of DNA cytosine-N4 methyltransferases: in vivo coexistence in the BcnI system and in vitro probing by hybrid formation. Nucleic Acids Research. 30(7). 1547–1557. 11 indexed citations
16.
Klimašauskas, Saulius, Rūta Gerasimaitė, Giedrius Vilkaitis, & Saulius Kulakauskas. (2002). N4,5-dimethylcytosine, a novel hypermodified base in DNA. Nucleic Acids Symposium Series. 2(1). 73–74. 5 indexed citations
17.
Vilkaitis, Giedrius, et al.. (2001). The Mechanism of DNA Cytosine-5 Methylation. Journal of Biological Chemistry. 276(24). 20924–20934. 97 indexed citations
18.
Vilkaitis, Giedrius, Aiping Dong, Elmar G. Weinhold, Xiaodong Cheng, & Saulius Klimašauskas. (2000). Functional Roles of the Conserved Threonine 250 in the Target Recognition Domain of HhaI DNA Methyltransferase. Journal of Biological Chemistry. 275(49). 38722–38730. 65 indexed citations
19.
Vilkaitis, Giedrius & Saulius Klimašauskas. (1999). Bisulfite Sequencing Protocol Displays both 5-Methylcytosine and N4-Methylcytosine. Analytical Biochemistry. 271(1). 116–119. 27 indexed citations
20.
Vilkaitis, Giedrius, et al.. (1995). Identification of a gene encoding a DNA invertase-like enzyme adjacent to the PaeR7I restriction-modification system. Gene. 157(1-2). 81–84. 27 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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