Anne E. d’Aquino

400 total citations
10 papers, 279 citations indexed

About

Anne E. d’Aquino is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Anne E. d’Aquino has authored 10 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Oncology. Recurrent topics in Anne E. d’Aquino's work include RNA and protein synthesis mechanisms (8 papers), RNA modifications and cancer (7 papers) and Bacterial Genetics and Biotechnology (4 papers). Anne E. d’Aquino is often cited by papers focused on RNA and protein synthesis mechanisms (8 papers), RNA modifications and cancer (7 papers) and Bacterial Genetics and Biotechnology (4 papers). Anne E. d’Aquino collaborates with scholars based in United States. Anne E. d’Aquino's co-authors include Michael C. Jewett, Do Soon Kim, Teresa Szal, Alexander S. Mankin, Nikolay A. Aleksashin, Erik D. Carlson, Kim L. Hoang, Nora Vázquez‐Laslop, Filippo Caschera and Norman H. Packard and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Nature Nanotechnology.

In The Last Decade

Anne E. d’Aquino

10 papers receiving 277 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anne E. d’Aquino United States	8	258	53	23	21	14	10	279
Heyuan Qi China	8	203 0.8×	49 0.9×	18 0.8×	4 0.2×	10 0.7×	13	234
Robert E. Dewhurst Australia	4	154 0.6×	76 1.4×	29 1.3×	6 0.3×	2 0.1×	4	183
Jeremy Heil United States	5	214 0.8×	256 4.8×	16 0.7×	5 0.2×	9 0.6×	7	358
Ed Belouski United States	6	198 0.8×	33 0.6×	3 0.1×	11 0.5×	3 0.2×	8	237
Thadeous J. Kacmarczyk United States	6	216 0.8×	89 1.7×	51 2.2×	2 0.1×	6 0.4×	7	265
Irene López‐Perolio Spain	5	107 0.4×	38 0.7×	30 1.3×	24 1.1×	1 0.1×	5	150
Jacob M. Tome United States	6	416 1.6×	52 1.0×	6 0.3×	5 0.2×	2 0.1×	7	449
Ioanna Tzani Ireland	7	253 1.0×	23 0.4×	8 0.3×	5 0.2×	2 0.1×	10	275
Karim El Soufi France	6	132 0.5×	26 0.5×	17 0.7×	7 0.3×	3 0.2×	8	197
Eva Harreither Austria	5	167 0.6×	47 0.9×	3 0.1×	18 0.9×		7	185

Countries citing papers authored by Anne E. d’Aquino

Since Specialization

Citations

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

Fields of papers citing papers by Anne E. d’Aquino

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anne E. d’Aquino. 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 Anne E. d’Aquino. The network helps show where Anne E. d’Aquino may publish in the future.

Co-authorship network of co-authors of Anne E. d’Aquino

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

All Works

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10 of 10 papers shown

1.

Jung, Jaeyoung K., Joseph J. Muldoon, Maria D. Cabezas, et al.. (2024). Developing, Characterizing, and Modeling CRISPR-Based Point-of-Use Pathogen Diagnostics. ACS Synthetic Biology. 14(1). 129–147. 5 indexed citations

2.

Krüger, Antje, Andrew M. Watkins, Roger Wellington-Oguri, et al.. (2023). Community science designed ribosomes with beneficial phenotypes. Nature Communications. 14(1). 961–961. 9 indexed citations

3.

Aleksashin, Nikolay A., Teresa Szal, Anne E. d’Aquino, et al.. (2020). A fully orthogonal system for protein synthesis in bacterial cells. Nature Communications. 11(1). 1858–1858. 43 indexed citations

4.

d’Aquino, Anne E., et al.. (2020). Mutational characterization and mapping of the 70S ribosome active site. Nucleic Acids Research. 48(5). 2777–2789. 29 indexed citations

5.

Carlson, Erik D., Anne E. d’Aquino, Do Soon Kim, et al.. (2019). Engineered ribosomes with tethered subunits for expanding biological function. Nature Communications. 10(1). 3920–3920. 55 indexed citations

6.

Yesselman, Joseph D., Daniel Eiler, Erik D. Carlson, et al.. (2019). Computational design of three-dimensional RNA structure and function. Nature Nanotechnology. 14(9). 866–873. 49 indexed citations

7.

Smith, Ian W. M., Anne E. d’Aquino, Andrew Fedanov, et al.. (2019). The 3.2 Å structure of a bioengineered variant of blood coagulation factor VIII indicates two conformations of the C2 domain. Journal of Thrombosis and Haemostasis. 18(1). 57–69. 17 indexed citations

8.

d’Aquino, Anne E., et al.. (2019). Mutating the Ribosome Peptidyl Transferase Center In Vitro. The FASEB Journal. 33(S1). 1 indexed citations

9.

d’Aquino, Anne E., Do Soon Kim, & Michael C. Jewett. (2018). Engineered Ribosomes for Basic Science and Synthetic Biology. Annual Review of Chemical and Biomolecular Engineering. 9(1). 311–340. 37 indexed citations

10.

Caschera, Filippo, et al.. (2018). High-Throughput Optimization Cycle of a Cell-Free Ribosome Assembly and Protein Synthesis System. ACS Synthetic Biology. 7(12). 2841–2853. 34 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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