Charles W. Carter

11.3k total citations · 1 hit paper
178 papers, 8.2k citations indexed

About

Charles W. Carter is a scholar working on Molecular Biology, Materials Chemistry and Genetics. According to data from OpenAlex, Charles W. Carter has authored 178 papers receiving a total of 8.2k indexed citations (citations by other indexed papers that have themselves been cited), including 111 papers in Molecular Biology, 37 papers in Materials Chemistry and 23 papers in Genetics. Recurrent topics in Charles W. Carter's work include RNA and protein synthesis mechanisms (78 papers), Protein Structure and Dynamics (33 papers) and Enzyme Structure and Function (33 papers). Charles W. Carter is often cited by papers focused on RNA and protein synthesis mechanisms (78 papers), Protein Structure and Dynamics (33 papers) and Enzyme Structure and Function (33 papers). Charles W. Carter collaborates with scholars based in United States, New Zealand and France. Charles W. Carter's co-authors include I. H. Suffet, Richard Wolfenden, Steven A. Rosenberg, Steven A. Short, Peter R. Wills, Joseph Kraut, Paul Aebersold, James Chih‐Hsin Yang, Colleen Simpson and Diane Solomon and has published in prestigious journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Charles W. Carter

165 papers receiving 7.9k citations

Hit Papers

Use of Tumor-Infiltrating Lymphocytes and Interleukin-2 i... 1988 2026 2000 2013 1988 500 1000 1.5k

Peers

Charles W. Carter
Jeremy M Berg United States
M.S. Weiss Germany
Benjamin G. Davis United Kingdom
Thomas R. Cech United States
Lawrence A. Loeb United States
Chung‐Jung Tsai United States
David Ginsburg United States
Charles W. Carter
Citations per year, relative to Charles W. Carter Charles W. Carter (= 1×) peers Vladimir Baranov

Countries citing papers authored by Charles W. Carter

Since Specialization
Citations

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

Fields of papers citing papers by Charles W. Carter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles W. Carter. 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 Charles W. Carter. The network helps show where Charles W. Carter may publish in the future.

Co-authorship network of co-authors of Charles W. Carter

This figure shows the co-authorship network connecting the top 25 collaborators of Charles W. Carter. A scholar is included among the top collaborators of Charles W. Carter 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 Charles W. Carter. Charles W. Carter 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.
Kuhlman, Brian, et al.. (2025). Aminoacyl-tRNA synthetase urzymes optimized by deep learning behave as a quasispecies. Structural Dynamics. 12(2). 24701–24701. 1 indexed citations
2.
Weinreb, Violetta, Gabriel E. Weinreb, & Charles W. Carter. (2023). High-throughput thermal denaturation of tryptophanyl-tRNA synthetase combinatorial mutants reveals high-order energetic coupling determinants of conformational stability. Structural Dynamics. 10(4). 44304–44304. 1 indexed citations
3.
Tang, Guo Qing, et al.. (2023). Domain acquisition by class I aminoacyl-tRNA synthetase urzymes coordinated the catalytic functions of HVGH and KMSKS motifs. Nucleic Acids Research. 51(15). 8070–8084. 10 indexed citations
4.
Preiss, Alexander, Emily Hadley, Marie C. D. Stoner, et al.. (2022). Incorporation of near-real-time hospital occupancy data to improve hospitalization forecast accuracy during the COVID-19 pandemic. Infectious Disease Modelling. 7(1). 277–285. 6 indexed citations
5.
Williams, Tishan, et al.. (2014). Did Class 1 and Class 2 Aminoacyl Trna Synthetases Descend from Genetically Complimentary, Catalytically Active ATP-Binding Motifs?. Biophysical Journal. 106(2). 675a–675a. 3 indexed citations
6.
Weinreb, Violetta, Li Li, Srinivas Niranj Chandrasekaran, et al.. (2014). Enhanced Amino Acid Selection in Fully Evolved Tryptophanyl-tRNA Synthetase, Relative to Its Urzyme, Requires Domain Motion Sensed by the D1 Switch, a Remote Dynamic Packing Motif. Journal of Biological Chemistry. 289(7). 4367–4376. 30 indexed citations
7.
Chandrasekaran, Srinivas Niranj, et al.. (2013). Statistical Evaluation of the Rodin–Ohno Hypothesis: Sense/Antisense Coding of Ancestral Class I and II Aminoacyl-tRNA Synthetases. Molecular Biology and Evolution. 30(7). 1588–1604. 37 indexed citations
8.
Li, Li & Charles W. Carter. (2013). Full Implementation of the Genetic Code by Tryptophanyl-tRNA Synthetase Requires Intermodular Coupling. Journal of Biological Chemistry. 288(48). 34736–34745. 30 indexed citations
9.
Li, Li, Violetta Weinreb, Christopher S. Francklyn, & Charles W. Carter. (2011). Histidyl-tRNA Synthetase Urzymes. Journal of Biological Chemistry. 286(12). 10387–10395. 47 indexed citations
10.
Rodin, Andréi S., Sergei N. Rodin, & Charles W. Carter. (2009). On Primordial Sense–Antisense Coding. Journal of Molecular Evolution. 69(5). 555–67. 33 indexed citations
11.
Carter, Charles W.. (2009). E Pluribus Tres: The 2009 Nobel Prize in Chemistry. Structure. 17(12). 1558–1561. 1 indexed citations
12.
Li, Li, et al.. (2007). A Minimal TrpRS Catalytic Domain Supports Sense/Antisense Ancestry of Class I and II Aminoacyl-tRNA Synthetases. Molecular Cell. 25(6). 851–862. 74 indexed citations
13.
Bishop, Michael, Daniel H. Fowler, Kathleen M. Castro, et al.. (2004). Allogeneic Lymphocytes Induce Tumor Regression of Advanced Metastatic Breast Cancer. Journal of Clinical Oncology. 22(19). 3886–3892. 74 indexed citations
14.
Rould, Mark A. & Charles W. Carter. (2003). Isomorphous Difference Methods. Methods in enzymology on CD-ROM/Methods in enzymology. 374. 145–163. 20 indexed citations
15.
Kang, Elizabeth M., Moniek de Witte, Harry L. Malech, et al.. (2002). Gene Therapy–based Treatment for HIV-Positive Patients with Malignancies. Journal of Hematotherapy & Stem Cell Research. 11(5). 809–816. 15 indexed citations
16.
Carter, Charles W., et al.. (2001). Four-body potentials reveal protein-specific correlations to stability changes caused by hydrophobic core mutations. Journal of Molecular Biology. 311(4). 625–638. 97 indexed citations
17.
Halverson, David, Gretchen N. Schwartz, Charles W. Carter, Ronald E. Gress, & Daniel H. Fowler. (1997). In Vitro Generation of Allospecific Human CD8+ T Cells of Tc1 and Tc2 Phenotype. Blood. 90(5). 2089–2096. 39 indexed citations
18.
Carter, Charles W.. (1995). Entropy, likelihood and phase determination. Structure. 3(2). 147–150. 2 indexed citations
19.
Carter, Charles W., et al.. (1993). Entropy maximization constrained by solvent flatness: a new method for macromolecular phase extension and map improvement. Acta Crystallographica Section D Biological Crystallography. 49(1). 193–212. 17 indexed citations
20.
Bukovský, Antonín, Carlos A. Labarrere, Charles W. Carter, B. Haag, & W. Pagé Faulk. (1992). NOVEL IMMUNOHISTOCHEMICAL MARKERS OF HUMAN RENAL ALLOGRAFT DYSFUNCTION—ANTITHROMBIN III, THY-1, UROKINASE, AND ALPHA–SMOOTH MUSCLE ACTIN. Transplantation. 54(6). 1064–1070. 9 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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