Amanda Wakefield

2.4k citations
18 papers · 501 · h-index 10

Impact in

Papers in

    • Protein Structure and Dynamics 6
    • Receptor Mechanisms and Signaling 3
    • Chemical Synthesis and Analysis 2
    • CAR-T cell therapy research 3

Amanda Wakefield

17 papers receiving 494 citations

Peers

Amanda Wakefield
Comparison fields: 5 of 77
  • Computational Theory and Mathematics 170
  • Molecular Biology 371
  • Oncology 57
  • Radiology, Nuclear Medicine and Imaging 48
  • Spectroscopy 38
Replace António J. Preto with:
António J. Preto Portugal
Samuel DeLuca United States
Sameh Eid Egypt
Brandon S. Zerbe United States
Christina Schindler Germany
Gregory D. Friedland United States
Raphaël Bourgeas France
Yuichiro Hourai Japan
Stefania Pfeiffer‐Marek Germany
Özge Şensoy Türkiye
Amanda Wakefield relative to António J. Preto Portugal António J. Preto's profile →
Citations per field
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António J. Preto · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Amanda Wakefield, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Amanda Wakefield Line = papers co-authored together Amanda Wakefield links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2018128
2 201898
3 201546
4 201939
5 202135
6 201933
7 202229
8 201524
9 201918
10 202214
11 20149
12 20209
13 20158
14 20214
15 20144
16 20151
17 20221
18
An insight into adolescent transition from rural to urban centres
20041

About Amanda Wakefield

Amanda Wakefield is a scholar working on Molecular Biology, Oncology, Computational Theory and Mathematics, Materials Chemistry and Cellular and Molecular Neuroscience, having authored 18 papers that have together received 501 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (5 papers), Receptor Mechanisms and Signaling (3 papers), CAR-T cell therapy research (3 papers), Enzyme Structure and Function (3 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Chemical Synthesis and Analysis (2 papers) and Neuropeptides and Animal Physiology (2 papers). The work is most often cited by research in Computational Theory and Mathematics (170 citations), Molecular Biology (371 citations), Oncology (57 citations), Radiology, Nuclear Medicine and Imaging (48 citations) and Spectroscopy (38 citations). Amanda Wakefield has collaborated with scholars based in United States, Hungary and Brazil. Frequent co-authors include Sándor Vajda, Dmitri Beglov, Adrian Whitty, Dima Kozakov, Megan Egbert, György M. Keserű, Vincent A. Voelz, William M. Wuest, Karen N. Allen and Lingqi Luo. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal for ImmunoTherapy of Cancer, Molecular Therapy, Journal of Neuro-Oncology and Biochemistry.

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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