David G. Lambert

10.5k citations
302 papers · 7.7k · h-index 46

Impact in

Papers in

    • Neuropeptides and Animal Physiology 135
    • Neuroscience and Neuropharmacology Research 43
    • Receptor Mechanisms and Signaling 139
    • Ion channel regulation and function 38
    • Pharmacological Receptor Mechanisms and Effects 25

David G. Lambert

295 papers receiving 7.5k citations

Peers

David G. Lambert
Comparison fields: 5 of 159
  • Cellular and Molecular Neuroscience 4.4k
  • Physiology 1.6k
  • Anesthesiology and Pain Medicine 298
  • Molecular Biology 3.9k
  • Pharmacology 826
Replace John A. Peters with:
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J.A. Strong United States
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Girolamo Calò Italy
Yu‐Qiu Zhang China
Roger J. Summers Australia
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Citations per field
00.5×1.6×
John A. Peters · 1×
Citations per year

Countries citing papers authored by David G. Lambert

Since Specialization
Citations

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

Fields of papers citing papers by David G. Lambert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David G. Lambert. 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 David G. Lambert. The network helps show where David G. Lambert may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 302 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008298
2 1969213
3 2000169
4 2002148
5 2013141
6 2003138
7 1990137
8 2009130
9 1996121
10 2011116
11 1989113
12 2014106
13 1999101
14 199198
15 201995
16 200093
17 200987
18 199686
19 201485
20 200083

About David G. Lambert

David G. Lambert is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Physiology, Surgery and Pharmacology, having authored 302 papers that have together received 7.7k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (139 papers), Neuropeptides and Animal Physiology (135 papers), Neuroscience and Neuropharmacology Research (43 papers), Pain Mechanisms and Treatments (41 papers), Ion channel regulation and function (38 papers), Pharmacological Receptor Mechanisms and Effects (25 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (22 papers) and Hypothalamic control of reproductive hormones (17 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (4.4k citations), Physiology (1.6k citations), Anesthesiology and Pain Medicine (298 citations), Molecular Biology (3.9k citations) and Pharmacology (826 citations). David G. Lambert has collaborated with scholars based in United Kingdom, Italy and United States. Frequent co-authors include David J. Rowbotham, Girolamo Calò, Stefan R. Nahorski, Remo Guerrini, D Smart, Jonathan P. Thompson, J. McDonald, Darren Smart, Severo Salvadori and John McDonald. Their work appears in journals such as British Journal of Anaesthesia, British Journal of Pharmacology, Naunyn-Schmiedeberg s Archives of Pharmacology, Biochemical Society Transactions and PLoS ONE.

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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