Malcolm Campbell

3.8k citations
83 papers · 2.2k · h-index 25

Impact in

Papers in

Malcolm Campbell

81 papers receiving 2.0k citations

Peers

Malcolm Campbell
Comparison fields: 5 of 150
  • Cognitive Neuroscience 491
  • Cardiology and Cardiovascular Medicine 282
  • Cellular and Molecular Neuroscience 185
  • Psychiatry and Mental health 137
  • Clinical Psychology 162
Replace Kelly Jones with:
Kelly Jones New Zealand
Hiroshi Fukuda Japan
Terry Reed United States
Janet M. Grubber United States
Marinella Coco Italy
Fuquan Zhang China
Elizabeth Wells United States
Fred S. Mishkin United States
Marilyn G. Klug United States
Anton N. Hasso United States
Malcolm Campbell relative to Kelly Jones New Zealand Kelly Jones's profile →
Citations per field
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Citations per year

Countries citing papers authored by Malcolm Campbell

Since Specialization
Citations

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

Fields of papers citing papers by Malcolm Campbell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994241
2 2009153
3 1952113
4 2018106
5 195688
6 197877
7 201167
8 200864
9 200564
10 200459
11 195459
12 200751
13 200345
14 201242
15 200641
16 201639
17 201837
18 201334
19 201834
20 201531

About Malcolm Campbell

Malcolm Campbell is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Molecular Biology, Cardiology and Cardiovascular Medicine and Pediatrics, Perinatology and Child Health, having authored 83 papers that have together received 2.2k indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (7 papers), Hearing Impairment and Communication (5 papers), Neural dynamics and brain function (5 papers), Neuropeptides and Animal Physiology (5 papers), Global Maternal and Child Health (4 papers), Autism Spectrum Disorder Research (4 papers), Neuroscience and Neuropharmacology Research (3 papers) and Protein Kinase Regulation and GTPase Signaling (3 papers). The work is most often cited by research in Cognitive Neuroscience (491 citations), Cardiology and Cardiovascular Medicine (282 citations), Cellular and Molecular Neuroscience (185 citations), Psychiatry and Mental health (137 citations) and Clinical Psychology (162 citations). Malcolm Campbell has collaborated with scholars based in United Kingdom, United States and Nigeria. Frequent co-authors include Elisabeth R. Trimble, Karen Luker, Lisa M. Giocomo, Gretl A. McHugh, Chris Todd, Charles Baker, P. Wood, Russell Brock, B. Nave and Jon Lindstrom. Their work appears in journals such as Midwifery, Heart, Neuron, Circulation Research and Journal of Innovation in Health Informatics.

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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