Amanda Wakefield

2.3k total citations
18 papers, 461 citations indexed

About

Amanda Wakefield is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Amanda Wakefield has authored 18 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Oncology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Amanda Wakefield's work include Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (5 papers) and CAR-T cell therapy research (3 papers). Amanda Wakefield is often cited by papers focused on Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (5 papers) and CAR-T cell therapy research (3 papers). Amanda Wakefield collaborates with scholars based in United States, Hungary and Austria. Amanda Wakefield's co-authors include Sándor Vajda, Dmitri Beglov, Adrian Whitty, Dima Kozakov, Megan Egbert, William M. Wuest, György M. Keserű, Karen N. Allen, Vincent A. Voelz and Lingqi Luo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Amanda Wakefield

17 papers receiving 455 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Amanda Wakefield United States 10 359 160 58 49 43 18 461
Paul Zuck United States 15 316 0.9× 111 0.7× 47 0.8× 38 0.8× 17 0.4× 30 523
António J. Preto Portugal 12 290 0.8× 114 0.7× 34 0.6× 30 0.6× 28 0.7× 24 424
William A. McLaughlin United States 10 522 1.5× 145 0.9× 50 0.9× 59 1.2× 93 2.2× 22 651
Samuel DeLuca United States 6 458 1.3× 76 0.5× 42 0.7× 84 1.7× 117 2.7× 8 632
Christina Schindler Germany 15 676 1.9× 167 1.0× 47 0.8× 60 1.2× 149 3.5× 25 822
Joerg Bomke Germany 6 365 1.0× 127 0.8× 33 0.6× 30 0.6× 56 1.3× 8 496
Stephen Boulton Canada 17 539 1.5× 94 0.6× 53 0.9× 18 0.4× 47 1.1× 29 706
Brandon S. Zerbe United States 9 488 1.4× 203 1.3× 47 0.8× 35 0.7× 129 3.0× 12 610
Anna C. Salzberg United States 4 510 1.4× 353 2.2× 40 0.7× 35 0.7× 60 1.4× 5 633
Özge Şensoy Türkiye 12 299 0.8× 78 0.5× 38 0.7× 23 0.5× 45 1.0× 32 448

Countries citing papers authored by Amanda Wakefield

Since Specialization
Citations

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

Fields of papers citing papers by Amanda Wakefield

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amanda Wakefield

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

All Works

18 of 18 papers shown
1.
Wakefield, Amanda, Dima Kozakov, & Sándor Vajda. (2022). Mapping the binding sites of challenging drug targets. Current Opinion in Structural Biology. 75. 102396–102396. 26 indexed citations
2.
Jones, George, et al.. (2022). API Development Increases Access to Shared Computing Resources at Boston University. Journal of Software Engineering and Applications. 15(6). 197–207. 1 indexed citations
3.
Wakefield, Amanda, Dávid Bajusz, Dima Kozakov, György M. Keserű, & Sándor Vajda. (2022). Conservation of Allosteric Ligand Binding Sites in G-Protein Coupled Receptors. Journal of Chemical Information and Modeling. 62(20). 4937–4954. 13 indexed citations
4.
Bajusz, Dávid, Warren S. Wade, Grzegorz Satała, et al.. (2021). Exploring protein hotspots by optimized fragment pharmacophores. Nature Communications. 12(1). 3201–3201. 31 indexed citations
5.
Nielsen, Alexander L., Lucy Lin, N.R. Silvaggi, et al.. (2021). Use of Crystallography and Molecular Modeling for the Inhibition of the Botulinum Neurotoxin A Protease. ACS Medicinal Chemistry Letters. 12(8). 1318–1324. 4 indexed citations
6.
Wakefield, Amanda, Christine Yueh, Dmitri Beglov, et al.. (2020). Benchmark Sets for Binding Hot Spot Identification in Fragment-Based Ligand Discovery. Journal of Chemical Information and Modeling. 60(12). 6612–6623. 9 indexed citations
7.
Wakefield, Amanda, Jonathan S. Mason, Sándor Vajda, & György M. Keserű. (2019). Analysis of tractable allosteric sites in G protein-coupled receptors. Scientific Reports. 9(1). 6180–6180. 36 indexed citations
8.
9.
Wakefield, Amanda, et al.. (2019). Structure-Based Analysis of Cryptic-Site Opening. Structure. 28(2). 223–235.e2. 17 indexed citations
10.
Beglov, Dmitri, David Hall, Amanda Wakefield, et al.. (2018). Exploring the structural origins of cryptic sites on proteins. Proceedings of the National Academy of Sciences. 115(15). E3416–E3425. 93 indexed citations
11.
Vajda, Sándor, Dmitri Beglov, Amanda Wakefield, Megan Egbert, & Adrian Whitty. (2018). Cryptic binding sites on proteins: definition, detection, and druggability. Current Opinion in Chemical Biology. 44. 1–8. 114 indexed citations
12.
Wakefield, Amanda, Antonella Pignata, Alexia Ghazi, et al.. (2015). Is CMV a target in pediatric glioblastoma? Expression of CMV proteins, pp65 and IE1-72 and CMV nucleic acids in a cohort of pediatric glioblastoma patients. Journal of Neuro-Oncology. 125(2). 307–315. 24 indexed citations
13.
Hegde, Meenakshi, Zakaria Grada, Antonella Pignata, et al.. (2015). A bispecific chimeric antigen receptor molecule enhances T cell activation through dual immunological synapse formation and offsets antigen escape in glioblastoma. Journal for ImmunoTherapy of Cancer. 3(S2). 6 indexed citations
14.
Byrd, Tiara T., Kristen Fousek, Antonella Pignata, et al.. (2015). 720. Triple-Negative Breast Cancer Cells and Tumor Endothelium Are Killed by Targeting Tumor Endothelial Marker 8 (TEM8). Molecular Therapy. 23. S287–S288. 1 indexed citations
15.
Wakefield, Amanda, William M. Wuest, & Vincent A. Voelz. (2015). Molecular Simulation of Conformational Pre-Organization in Cyclic RGD Peptides. Journal of Chemical Information and Modeling. 55(4). 806–813. 42 indexed citations
16.
Hegde, Meenakshi, Amanda Wakefield, Vita S. Brawley, et al.. (2014). Genetic modification of T cells with a novel bispecific chimeric antigen receptor to enhance the control of high-grade glioma (HGG).. Journal of Clinical Oncology. 32(15_suppl). 10027–10027. 9 indexed citations
17.
Byrd, Tiara T., Kristen Fousek, Antonella Pignata, et al.. (2014). TEM8 specific T cells target the tumor cells and tumor-associated vasculature in triple negative breast cancer. Journal for ImmunoTherapy of Cancer. 2(S3). 4 indexed citations
18.
Bramston, Paul, et al.. (2004). An insight into adolescent transition from rural to urban centres. University of Southern Queensland ePrints (University of Southern Queensland). 1 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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