Neil Shaw

4.4k citations
96 papers · 3.0k · 1 hit paper · h-index 29

Impact in

Papers in

Neil Shaw

94 papers receiving 2.9k citations

Neil Shaw's Hit Papers

Structural basis and functional analysis of the SARS coronavirus nsp14–nsp10 complex 2015 · 348 citations
3480+3+7Years since publication100200300

Peers

Neil Shaw
Comparison fields: 5 of 148
  • Infectious Diseases 628
  • Immunology 454
  • Cognitive Neuroscience 392
  • Neurology 242
  • Molecular Biology 1.1k
Replace Alexander V. Ivanov with:
Alexander V. Ivanov Russia
Koichi Ishikawa Japan
Ismo Ulmanen Finland
Mariko Saito Japan
Weiping Zhang China
Peter Williamson Australia
Masahiro Kondo Japan
Takeshi Shimizu Japan
Nigel Garrett South Africa
Hua Yang China
Neil Shaw relative to Alexander V. Ivanov Russia Alexander V. Ivanov's profile →
Citations per field
00.5×1.5×
Alexander V. Ivanov · 1×
Citations per year

Countries citing papers authored by Neil Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Neil Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Neil Shaw, 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 Neil Shaw Line = papers co-authored together Neil Shaw links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 96 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Structural basis and functional analysis of the SARS coronavirus nsp14–nsp10 complex
Hit paper breakdown →
2015348
2 2012285
3 2017121
4 1986104
5 1962103
6 1988102
7 197994
8 201487
9 201367
10 196367
11 200766
12 198665
13 200757
14 198257
15 201353
16 198052
17 197852
18 200950
19 201043
20 201442

About Neil Shaw

Neil Shaw is a scholar working on Molecular Biology, Cognitive Neuroscience, Materials Chemistry, Infectious Diseases and Neurology, having authored 96 papers that have together received 3.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (15 papers), EEG and Brain-Computer Interfaces (12 papers), Enzyme Structure and Function (11 papers), Traumatic Brain Injury and Neurovascular Disturbances (10 papers), Biochemical and Molecular Research (10 papers), Folate and B Vitamins Research (9 papers), Porphyrin Metabolism and Disorders (8 papers) and Traumatic Brain Injury Research (7 papers). The work is most often cited by research in Infectious Diseases (628 citations), Immunology (454 citations), Cognitive Neuroscience (392 citations), Neurology (242 citations) and Molecular Biology (1.1k citations). Neil Shaw has collaborated with scholars based in China, New Zealand and United States. Frequent co-authors include B.R Cant, Ann L. Hume, A. W. Johnson, Rongguang Zhang, Zhi‐Jie Liu, Zihe Rao, Songying Ouyang, E. Lester Smith, Leonard Mervyn and Zhiyong Lou. Their work appears in journals such as Electroencephalography and Clinical Neurophysiology, The FASEB Journal, Protein & Cell, Physiology & Behavior and Proteins Structure Function and Bioinformatics.

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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