John C. Chaput

6.8k total citations · 2 hit papers
132 papers, 5.4k citations indexed

About

John C. Chaput is a scholar working on Molecular Biology, Ecology and Genetics. According to data from OpenAlex, John C. Chaput has authored 132 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Molecular Biology, 15 papers in Ecology and 10 papers in Genetics. Recurrent topics in John C. Chaput's work include Advanced biosensing and bioanalysis techniques (76 papers), DNA and Nucleic Acid Chemistry (62 papers) and RNA and protein synthesis mechanisms (59 papers). John C. Chaput is often cited by papers focused on Advanced biosensing and bioanalysis techniques (76 papers), DNA and Nucleic Acid Chemistry (62 papers) and RNA and protein synthesis mechanisms (59 papers). John C. Chaput collaborates with scholars based in United States, Belgium and China. John C. Chaput's co-authors include Matthew R. Dunn, Randi M. Jimenez, Hanyang Yu, Christopher Switzer, Jack W. Szostak, Piet Herdewijn, Berea A. R. Williams, Ali Nikoomanzar, Su Zhang and Sujay P. Sau and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

John C. Chaput

128 papers receiving 5.4k citations

Hit Papers

Analysis of aptamer discovery and technology 2012 2026 2016 2021 2017 2012 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John C. Chaput United States 36 5.0k 985 603 311 288 132 5.4k
Shu‐ichi Nakano Japan 30 4.4k 0.9× 365 0.4× 539 0.9× 66 0.2× 129 0.4× 100 4.7k
Joseph A. Piccirilli United States 46 6.1k 1.2× 160 0.2× 521 0.9× 244 0.8× 771 2.7× 173 7.1k
Michiko Kimoto Japan 34 3.1k 0.6× 267 0.3× 276 0.5× 70 0.2× 353 1.2× 80 3.2k
Ichiro Hirao Japan 43 4.8k 1.0× 325 0.3× 489 0.8× 92 0.3× 1.4k 4.9× 215 6.0k
Luis A. Marky United States 42 6.6k 1.3× 454 0.5× 543 0.9× 27 0.1× 467 1.6× 126 7.4k
Christophe Danelon Netherlands 24 1.5k 0.3× 728 0.7× 129 0.2× 129 0.4× 106 0.4× 43 2.1k
Valentina Tereshko United States 39 3.6k 0.7× 377 0.4× 294 0.5× 25 0.1× 394 1.4× 58 4.4k
Anh Tuân Phan Singapore 59 13.0k 2.6× 391 0.4× 991 1.6× 25 0.1× 379 1.3× 151 13.5k
Yohei Yokobayashi Japan 28 2.5k 0.5× 389 0.4× 128 0.2× 299 1.0× 127 0.4× 76 2.8k
Timothy J. Wilson United Kingdom 31 2.3k 0.5× 209 0.2× 190 0.3× 60 0.2× 107 0.4× 76 2.8k

Countries citing papers authored by John C. Chaput

Since Specialization
Citations

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

Fields of papers citing papers by John C. Chaput

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John C. Chaput. 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 John C. Chaput. The network helps show where John C. Chaput may publish in the future.

Co-authorship network of co-authors of John C. Chaput

This figure shows the co-authorship network connecting the top 25 collaborators of John C. Chaput. A scholar is included among the top collaborators of John C. Chaput 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 John C. Chaput. John C. Chaput 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.
Chim, Nicholas, et al.. (2026). Rapid evolution of a highly efficient RNA polymerase by homologous recombination. Nature Chemical Biology.
2.
Lei, Li, Joel M. Harp, John C. Chaput, et al.. (2024). Structure and Stability of Ago2 MID‐Nucleotide Complexes: All‐in‐One (Drop) His6‐SUMO Tag Removal, Nucleotide Binding, and Crystal Growth. Current Protocols. 4(6). e1088–e1088.
3.
Apel, Cécile, Shaleen B. Korch, Florence Guérard, et al.. (2023). Metabolic adjustments in response to ATP spilling by the small DX protein in a Streptomyces strain. Frontiers in Cell and Developmental Biology. 11. 1129009–1129009. 3 indexed citations
4.
Chaput, John C., et al.. (2023). Engineering TNA polymerases through iterative cycles of directed evolution. Methods in enzymology on CD-ROM/Methods in enzymology. 691. 29–59. 5 indexed citations
5.
Paegel, Brian M., et al.. (2023). Highly Parallelized Screening of Functionally Enhanced XNA Aptamers in Uniform Hydrogel Particles. ACS Synthetic Biology. 12(7). 2127–2134. 10 indexed citations
6.
Chaput, John C., et al.. (2023). Stability and mechanism of threose nucleic acid toward acid-mediated degradation. Nucleic Acids Research. 51(18). 9542–9551. 14 indexed citations
7.
Chaput, John C., et al.. (2022). REVEALR-Based Genotyping of SARS-CoV-2 Variants of Concern in Clinical Samples. Journal of the American Chemical Society. 144(26). 11685–11692. 20 indexed citations
8.
Li, Qingfeng, et al.. (2021). Synthesis and Polymerase Recognition of Threose Nucleic Acid Triphosphates Equipped with Diverse Chemical Functionalities. Journal of the American Chemical Society. 143(42). 17761–17768. 31 indexed citations
9.
McCloskey, Cailen M., et al.. (2021). Evolution of Functionally Enhanced α-l-Threofuranosyl Nucleic Acid Aptamers. ACS Synthetic Biology. 10(11). 3190–3199. 27 indexed citations
10.
Nguyen, Kim, Yajun Wang, Whitney England, John C. Chaput, & Robert C. Spitale. (2021). Allele-Specific RNA Knockdown with a Biologically Stable and Catalytically Efficient XNAzyme. Journal of the American Chemical Society. 143(12). 4519–4523. 30 indexed citations
11.
Zhang, Li & John C. Chaput. (2020). In Vitro Selection of an ATP-Binding TNA Aptamer. Molecules. 25(18). 4194–4194. 22 indexed citations
12.
Dunn, Matthew R., et al.. (2020). Generating Biologically Stable TNA Aptamers that Function with High Affinity and Thermal Stability. Journal of the American Chemical Society. 142(17). 7721–7724. 93 indexed citations
13.
Chaput, John C. & Piet Herdewijn. (2019). Was ist XNA?. Angewandte Chemie. 131(34). 11694–11696. 10 indexed citations
14.
McCloskey, Cailen M., Jen-Yu Liao, Saikat Bala, & John C. Chaput. (2019). Ligase-Mediated Threose Nucleic Acid Synthesis on DNA Templates. ACS Synthetic Biology. 8(2). 282–286. 25 indexed citations
15.
Nikoomanzar, Ali, et al.. (2019). Elucidating the Determinants of Polymerase Specificity by Microfluidic-Based Deep Mutational Scanning. ACS Synthetic Biology. 8(6). 1421–1429. 31 indexed citations
16.
Bala, Saikat, et al.. (2018). Synthesis of 2′-Deoxy-α-l-threofuranosyl Nucleoside Triphosphates. The Journal of Organic Chemistry. 83(16). 8840–8850. 7 indexed citations
17.
Mei, Hui, Jen-Yu Liao, Randi M. Jimenez, et al.. (2018). Synthesis and Evolution of a Threose Nucleic Acid Aptamer Bearing 7-Deaza-7-Substituted Guanosine Residues. Journal of the American Chemical Society. 140(17). 5706–5713. 88 indexed citations
18.
Sau, Sujay P. & John C. Chaput. (2017). A Gram-Scale HPLC-Free Synthesis of TNA Triphosphates Using an Iterative Phosphorylation Strategy. Organic Letters. 19(16). 4379–4382. 15 indexed citations
19.
Nikoomanzar, Ali, Matthew R. Dunn, & John C. Chaput. (2017). Evaluating the Rate and Substrate Specificity of Laboratory Evolved XNA Polymerases. Analytical Chemistry. 89(23). 12622–12625. 17 indexed citations
20.
Pinheiro, Vitor B., Alexander I. Taylor, Christopher Cozens, et al.. (2012). Synthetic Genetic Polymers Capable of Heredity and Evolution. Science. 336(6079). 341–344. 546 indexed citations breakdown →

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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