Audronė Lapinaitė

1.9k total citations · 2 hit papers
15 papers, 1.3k citations indexed

About

Audronė Lapinaitė is a scholar working on Molecular Biology, Epidemiology and Genetics. According to data from OpenAlex, Audronė Lapinaitė has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 2 papers in Epidemiology and 2 papers in Genetics. Recurrent topics in Audronė Lapinaitė's work include CRISPR and Genetic Engineering (9 papers), RNA and protein synthesis mechanisms (8 papers) and RNA modifications and cancer (5 papers). Audronė Lapinaitė is often cited by papers focused on CRISPR and Genetic Engineering (9 papers), RNA and protein synthesis mechanisms (8 papers) and RNA modifications and cancer (5 papers). Audronė Lapinaitė collaborates with scholars based in United States, Germany and Lithuania. Audronė Lapinaitė's co-authors include Jennifer A. Doudna, Kevin T. Zhao, David R. Liu, Michelle F. Richter, Christopher Wilson, Luke W. Koblan, Gregory A. Newby, Jing Zeng, Daniel E. Bauer and Elliot O. Eton and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Audronė Lapinaitė

14 papers receiving 1.2k citations

Hit Papers

Phage-assisted evolution of an adenine base editor with i... 2020 2026 2022 2024 2020 2020 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Phage-assisted evolution of an adenine base editor with improved Cas domain compatibility and activity
    2020 633 citations Michelle F. Richter, Kevin T. Zhao et al. Nature Biotechnology profile →
  2. DNA capture by a CRISPR-Cas9–guided adenine base editor
    2020 130 citations Audronė Lapinaitė, Gavin J. Knott et al. Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Audronė Lapinaitė United States 10 1.2k 235 126 56 54 15 1.3k
Gianluca Petris Italy 17 857 0.7× 183 0.8× 52 0.4× 75 1.3× 15 0.3× 23 1.0k
John C. Manteiga United States 4 2.0k 1.7× 157 0.7× 214 1.7× 40 0.7× 12 0.2× 6 2.1k
Pilar Negrete Redondo Spain 12 731 0.6× 186 0.8× 100 0.8× 37 0.7× 11 0.2× 36 888
J. Ebert Germany 17 1.7k 1.4× 74 0.3× 106 0.8× 17 0.3× 39 0.7× 19 1.8k
Vincent Brondani Switzerland 12 1.0k 0.9× 196 0.8× 121 1.0× 27 0.5× 13 0.2× 17 1.2k
Antoine Cléry Switzerland 26 2.4k 2.0× 94 0.4× 150 1.2× 17 0.3× 37 0.7× 36 2.5k
Žaklina Strezoska United States 15 1.1k 1.0× 141 0.6× 74 0.6× 29 0.5× 10 0.2× 22 1.3k
William Selleck United States 12 1.8k 1.5× 177 0.8× 192 1.5× 8 0.1× 46 0.9× 12 1.9k
Kendall R Sanson United States 5 949 0.8× 160 0.7× 49 0.4× 27 0.5× 6 0.1× 5 1.1k
Matthew J. Schellenberg United States 19 1.2k 1.0× 85 0.4× 31 0.2× 15 0.3× 20 0.4× 34 1.2k

Countries citing papers authored by Audronė Lapinaitė

Since Specialization
Citations

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

Fields of papers citing papers by Audronė Lapinaitė

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Audronė Lapinaitė

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

All Works

15 of 15 papers shown
1.
Lapinaitė, Audronė, et al.. (2025). Preparation of high-purity RNPs of CRISPR-based DNA base editors. Methods in enzymology on CD-ROM/Methods in enzymology. 712. 277–315.
2.
Lapinaitė, Audronė, et al.. (2024). RNA-based programmable DNA cleavage. Nature Chemical Biology. 20(6). 664–665. 1 indexed citations
3.
Arantes, Pablo R., Xiaoyu Chen, Aakash Saha, et al.. (2024). Biophysical origin of adenine base editors’ improved editing efficiency. Biophysical Journal. 123(3). 340a–340a. 1 indexed citations
4.
Arantes, Pablo R., Xiaoyu Chen, Aakash Saha, et al.. (2024). Dimerization of the deaminase domain and locking interactions with Cas9 boost base editing efficiency in ABE8e. Nucleic Acids Research. 52(22). 13931–13944. 10 indexed citations
5.
Chen, Xiaoyu, et al.. (2023). Unlocking the secrets of ABEs: the molecular mechanism behind their specificity. Biochemical Society Transactions. 51(4). 1635–1646. 3 indexed citations
6.
Kellogg, Elizabeth H., Jonathan S. Gootenberg, Omar O. Abudayyeh, et al.. (2022). What are the current bottlenecks in developing and applying CRISPR technologies?. Cell Systems. 13(8). 589–593. 1 indexed citations
7.
Lapinaitė, Audronė, Gavin J. Knott, Enrique Lin-Shiao, et al.. (2020). DNA capture by a CRISPR-Cas9–guided adenine base editor. Science. 369(6503). 566–571. 130 indexed citations breakdown →
8.
Richter, Michelle F., Kevin T. Zhao, Elliot O. Eton, et al.. (2020). Phage-assisted evolution of an adenine base editor with improved Cas domain compatibility and activity. Nature Biotechnology. 38(7). 883–891. 633 indexed citations breakdown →
9.
Lapinaitė, Audronė, Teresa Carlomagno, & Frank Gabel. (2020). Small-Angle Neutron Scattering of RNA–Protein Complexes. Methods in molecular biology. 2113. 165–188. 14 indexed citations
10.
Lapinaitė, Audronė, Jennifer A. Doudna, & J.H.D. Cate. (2018). Programmable RNA recognition using a CRISPR-associated Argonaute. Proceedings of the National Academy of Sciences. 115(13). 3368–3373. 37 indexed citations
11.
Graziadei, Andrea, et al.. (2016). Archaea box C/D enzymes methylate two distinct substrate rRNA sequences with different efficiency. RNA. 22(5). 764–772. 10 indexed citations
12.
Kriukienė, Edita, Viviane Labrie, Tarang Khare, et al.. (2013). DNA unmethylome profiling by covalent capture of CpG sites. Nature Communications. 4(1). 2190–2190. 47 indexed citations
13.
Lapinaitė, Audronė, et al.. (2013). The structure of the box C/D enzyme reveals regulation of RNA methylation. Nature. 502(7472). 519–523. 136 indexed citations
14.
Lukinavičius, Gražvydas, et al.. (2012). Engineering the DNA cytosine-5 methyltransferase reaction for sequence-specific labeling of DNA. Nucleic Acids Research. 40(22). 11594–11602. 42 indexed citations
15.
Ballaré, Cecilia, Martin Lange, Audronė Lapinaitė, et al.. (2012). Phf19 links methylated Lys36 of histone H3 to regulation of Polycomb activity. Nature Structural & Molecular Biology. 19(12). 1257–1265. 186 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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