Chris Shaw
Impact in
- Microbiology top 0.05%
- Antimicrobial Peptides and Activities
- Aging top 1%
Papers in ⓘ
- Microbiology 171
- Antimicrobial Peptides and Activities 171
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- Neurobiology and Insect Physiology Research 73
- Neuropeptides and Animal Physiology 35
- Co-authors
- Tianbao Chen (130 shared papers)Mei Zhou (136 shared papers)Lei Wang (120 shared papers)D.W. Halton (34 shared papers)Aaron G. Maule (29 shared papers)Brian Walker (30 shared papers)Tianbao Chen (26 shared papers)Pingfan Rao (18 shared papers)
- Journals
- Peptides (42 papers)Regulatory Peptides (14 papers)Biochemical and Biophysical Research Communications (10 papers)Toxins (10 papers)Molecules (8 papers)
- Partner nations
- United KingdomChinaCanada
In The Last Decade
Chris Shaw
259 papers receiving 5.3k citations
Peers
Comparison fields: 5 of 120
- Microbiology 2.7k
- Aging 165
- Cellular and Molecular Neuroscience 1.7k
- Molecular Biology 3.1k
- Immunology 836
Countries citing papers authored by Chris Shaw
This map shows the geographic impact of Chris 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 Chris Shaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Shaw more than expected).
Fields of papers citing papers by Chris Shaw
This network shows the impact of papers produced by Chris 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 Chris Shaw. The network helps show where Chris Shaw may publish in the future.
Co-authors
The 25 scholars most cited alongside Chris Shaw, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 261 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 140 | |
| 2 | 2013 | 119 | |
| 3 | 1996 | 92 | |
| 4 | 1996 | 91 | |
| 5 | 2012 | 87 | |
| 6 | 2003 | 74 | |
| 7 | 1995 | 69 | |
| 8 | 2018 | 67 | |
| 9 | 1990 | 67 | |
| 10 | 1996 | 67 | |
| 11 | 2009 | 66 | |
| 12 | 1994 | 66 | |
| 13 | 2017 | 66 | |
| 14 | 1991 | 62 | |
| 15 | 2013 | 59 | |
| 16 | 2019 | 56 | |
| 17 | 2006 | 56 | |
| 18 | 2002 | 52 | |
| 19 | 2006 | 52 | |
| 20 | 2003 | 52 |
About Chris Shaw
Chris Shaw is a scholar working on Microbiology, Cellular and Molecular Neuroscience, Aging, Molecular Biology and Immunology, having authored 261 papers that have together received 5.4k indexed citations. Recurring topics across this work include Antimicrobial Peptides and Activities (171 papers), Biochemical and Structural Characterization (115 papers), Neurobiology and Insect Physiology Research (73 papers), Venomous Animal Envenomation and Studies (54 papers), Neuropeptides and Animal Physiology (35 papers), Amphibian and Reptile Biology (31 papers), Invertebrate Immune Response Mechanisms (23 papers) and Neuroendocrine regulation and behavior (17 papers). The work is most often cited by research in Microbiology (2.7k citations), Aging (165 citations), Cellular and Molecular Neuroscience (1.7k citations), Molecular Biology (3.1k citations) and Immunology (836 citations). Chris Shaw has collaborated with scholars based in United Kingdom, China and Canada. Frequent co-authors include Tianbao Chen, Mei Zhou, Lei Wang, D.W. Halton, Aaron G. Maule, Brian Walker, Tianbao Chen, Pingfan Rao, C.F. Johnston and Chengbang Ma. Their work appears in journals such as Peptides, Regulatory Peptides, Biochemical and Biophysical Research Communications, Toxins and Molecules.
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.